Table1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c47c1978",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import re\n",
    "import warnings\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sklearn\n",
    "# import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import tableone\n",
    "from utils import quick_load_liuzhong_health_check_data\n",
    "from plot_utils import plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "df_table1plus, l_consecute_man2p, l_consecute_man3p, df_table1plus_3p_revMM, df_meta_groups, rename_dict = quick_load_liuzhong_health_check_data()\n",
    "workdir = \"/cluster/home/bqhu_jh/projects/healthman/analysis/liuzhong/human/clinical/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ee2fe09d",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "l_high_lighted = list(df_meta_groups[\"item_id\"])\n",
    "l_columns = list(filter(lambda x: x[0]==\"v\", l_high_lighted))\n",
    "l_category = list(filter(lambda x: x[0]!=\"v\", l_high_lighted))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1ffda14a",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [],
   "source": [
    "mytable = tableone.TableOne(df_table1plus[df_table1plus[\"month\"].isin([12,1,2])], l_columns, [], \"year-month\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0411236b",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
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       "    .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>2020-12</th>\n",
       "      <th>2021-12</th>\n",
       "      <th>2022-12</th>\n",
       "      <th>2021-01</th>\n",
       "      <th>2022-01</th>\n",
       "      <th>2023-01</th>\n",
       "      <th>2021-02</th>\n",
       "      <th>2022-02</th>\n",
       "      <th>2023-02</th>\n",
       "      <th>Missing</th>\n",
       "      <th>Overall</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>item_name</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>心率</th>\n",
       "      <td>83.7 (13.4)</td>\n",
       "      <td>84.4 (13.1)</td>\n",
       "      <td>85.6 (13.3)</td>\n",
       "      <td>84.9 (13.0)</td>\n",
       "      <td>84.8 (12.4)</td>\n",
       "      <td>86.8 (13.2)</td>\n",
       "      <td>84.3 (12.9)</td>\n",
       "      <td>85.3 (12.4)</td>\n",
       "      <td>85.0 (12.2)</td>\n",
       "      <td>4569</td>\n",
       "      <td>84.8 (12.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>同型半胱氨酸</th>\n",
       "      <td>11.9 (6.7)</td>\n",
       "      <td>9.9 (4.6)</td>\n",
       "      <td>10.1 (4.3)</td>\n",
       "      <td>9.0 (4.5)</td>\n",
       "      <td>9.2 (4.0)</td>\n",
       "      <td>9.7 (2.9)</td>\n",
       "      <td>8.2 (3.9)</td>\n",
       "      <td>9.1 (3.7)</td>\n",
       "      <td>10.3 (4.2)</td>\n",
       "      <td>28513</td>\n",
       "      <td>9.6 (4.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>收缩压</th>\n",
       "      <td>123.9 (16.5)</td>\n",
       "      <td>124.5 (17.0)</td>\n",
       "      <td>124.0 (17.0)</td>\n",
       "      <td>121.1 (15.7)</td>\n",
       "      <td>119.7 (14.6)</td>\n",
       "      <td>122.1 (14.4)</td>\n",
       "      <td>120.5 (16.3)</td>\n",
       "      <td>121.3 (15.6)</td>\n",
       "      <td>121.8 (15.6)</td>\n",
       "      <td>4574</td>\n",
       "      <td>122.1 (16.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>舒张压</th>\n",
       "      <td>74.0 (10.7)</td>\n",
       "      <td>73.8 (10.9)</td>\n",
       "      <td>73.7 (10.8)</td>\n",
       "      <td>71.2 (10.2)</td>\n",
       "      <td>71.4 (10.0)</td>\n",
       "      <td>73.9 (9.6)</td>\n",
       "      <td>71.2 (10.4)</td>\n",
       "      <td>72.5 (10.5)</td>\n",
       "      <td>72.8 (10.3)</td>\n",
       "      <td>4571</td>\n",
       "      <td>72.7 (10.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甘油三酯</th>\n",
       "      <td>1.4 (1.3)</td>\n",
       "      <td>1.4 (1.0)</td>\n",
       "      <td>1.4 (1.1)</td>\n",
       "      <td>1.1 (0.9)</td>\n",
       "      <td>1.1 (0.9)</td>\n",
       "      <td>1.2 (0.9)</td>\n",
       "      <td>1.2 (1.0)</td>\n",
       "      <td>1.3 (1.1)</td>\n",
       "      <td>1.3 (1.2)</td>\n",
       "      <td>2516</td>\n",
       "      <td>1.3 (1.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总胆固醇</th>\n",
       "      <td>4.6 (0.9)</td>\n",
       "      <td>4.8 (0.9)</td>\n",
       "      <td>4.8 (1.0)</td>\n",
       "      <td>4.5 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.5 (0.9)</td>\n",
       "      <td>4.8 (0.9)</td>\n",
       "      <td>4.8 (0.9)</td>\n",
       "      <td>2517</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>高密度脂蛋白</th>\n",
       "      <td>1.3 (0.3)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>1.4 (0.3)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>2518</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>低密度脂蛋白</th>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2.7 (0.8)</td>\n",
       "      <td>2.8 (0.8)</td>\n",
       "      <td>2.5 (0.7)</td>\n",
       "      <td>2.5 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2.5 (0.7)</td>\n",
       "      <td>2.7 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2518</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>空腹血糖</th>\n",
       "      <td>5.1 (1.0)</td>\n",
       "      <td>5.0 (1.1)</td>\n",
       "      <td>5.0 (1.0)</td>\n",
       "      <td>4.9 (0.8)</td>\n",
       "      <td>4.8 (0.7)</td>\n",
       "      <td>4.9 (0.8)</td>\n",
       "      <td>4.8 (0.8)</td>\n",
       "      <td>5.0 (0.9)</td>\n",
       "      <td>4.9 (1.0)</td>\n",
       "      <td>668</td>\n",
       "      <td>4.9 (0.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>糖化血红蛋白A1</th>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>6.9 (0.8)</td>\n",
       "      <td>6.9 (0.8)</td>\n",
       "      <td>6.8 (0.7)</td>\n",
       "      <td>6.9 (0.8)</td>\n",
       "      <td>7.0 (0.9)</td>\n",
       "      <td>6.8 (0.6)</td>\n",
       "      <td>6.9 (0.8)</td>\n",
       "      <td>7.0 (0.9)</td>\n",
       "      <td>22037</td>\n",
       "      <td>6.9 (0.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>糖化血红蛋白A1c</th>\n",
       "      <td>5.8 (0.7)</td>\n",
       "      <td>5.7 (0.8)</td>\n",
       "      <td>5.7 (0.7)</td>\n",
       "      <td>5.6 (0.6)</td>\n",
       "      <td>5.7 (0.7)</td>\n",
       "      <td>5.8 (0.8)</td>\n",
       "      <td>5.6 (0.5)</td>\n",
       "      <td>5.7 (0.7)</td>\n",
       "      <td>5.8 (0.8)</td>\n",
       "      <td>22037</td>\n",
       "      <td>5.7 (0.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性粒细胞(%)</th>\n",
       "      <td>55.7 (8.3)</td>\n",
       "      <td>55.3 (8.2)</td>\n",
       "      <td>55.5 (8.4)</td>\n",
       "      <td>55.5 (8.5)</td>\n",
       "      <td>54.5 (8.7)</td>\n",
       "      <td>55.5 (8.5)</td>\n",
       "      <td>55.1 (8.4)</td>\n",
       "      <td>54.5 (8.4)</td>\n",
       "      <td>54.8 (8.1)</td>\n",
       "      <td>630</td>\n",
       "      <td>55.2 (8.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>淋巴细胞(%)</th>\n",
       "      <td>34.0 (7.7)</td>\n",
       "      <td>34.7 (7.7)</td>\n",
       "      <td>34.8 (7.9)</td>\n",
       "      <td>34.6 (7.9)</td>\n",
       "      <td>35.8 (8.1)</td>\n",
       "      <td>35.0 (7.8)</td>\n",
       "      <td>35.1 (7.9)</td>\n",
       "      <td>35.7 (7.9)</td>\n",
       "      <td>35.6 (7.6)</td>\n",
       "      <td>630</td>\n",
       "      <td>35.0 (7.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>单核细胞(%)</th>\n",
       "      <td>7.3 (1.7)</td>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>6.7 (1.8)</td>\n",
       "      <td>7.1 (1.7)</td>\n",
       "      <td>7.1 (1.6)</td>\n",
       "      <td>6.9 (1.7)</td>\n",
       "      <td>7.1 (1.6)</td>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>6.8 (1.6)</td>\n",
       "      <td>630</td>\n",
       "      <td>7.0 (1.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜碱性粒细胞(%)</th>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.5 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>630</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜酸性粒细胞(%)</th>\n",
       "      <td>2.3 (1.9)</td>\n",
       "      <td>2.4 (1.9)</td>\n",
       "      <td>2.4 (1.8)</td>\n",
       "      <td>2.1 (1.6)</td>\n",
       "      <td>2.1 (1.6)</td>\n",
       "      <td>2.1 (1.6)</td>\n",
       "      <td>2.2 (1.7)</td>\n",
       "      <td>2.2 (1.7)</td>\n",
       "      <td>2.3 (1.8)</td>\n",
       "      <td>630</td>\n",
       "      <td>2.2 (1.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>红细胞计数</th>\n",
       "      <td>4.8 (0.5)</td>\n",
       "      <td>4.8 (0.5)</td>\n",
       "      <td>4.8 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>630</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血小板计数</th>\n",
       "      <td>246.9 (57.3)</td>\n",
       "      <td>249.9 (57.8)</td>\n",
       "      <td>252.7 (57.4)</td>\n",
       "      <td>247.2 (57.0)</td>\n",
       "      <td>251.0 (57.7)</td>\n",
       "      <td>256.0 (63.3)</td>\n",
       "      <td>243.5 (57.5)</td>\n",
       "      <td>250.2 (56.6)</td>\n",
       "      <td>253.5 (58.0)</td>\n",
       "      <td>634</td>\n",
       "      <td>249.9 (57.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>白细胞计数</th>\n",
       "      <td>6.3 (1.6)</td>\n",
       "      <td>6.1 (1.6)</td>\n",
       "      <td>6.4 (1.6)</td>\n",
       "      <td>6.0 (1.5)</td>\n",
       "      <td>6.1 (1.6)</td>\n",
       "      <td>6.1 (1.5)</td>\n",
       "      <td>6.0 (1.5)</td>\n",
       "      <td>6.2 (1.6)</td>\n",
       "      <td>6.2 (1.6)</td>\n",
       "      <td>631</td>\n",
       "      <td>6.2 (1.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血红蛋白</th>\n",
       "      <td>145.5 (16.3)</td>\n",
       "      <td>143.8 (16.1)</td>\n",
       "      <td>143.8 (16.2)</td>\n",
       "      <td>139.5 (15.3)</td>\n",
       "      <td>138.3 (15.6)</td>\n",
       "      <td>136.5 (14.7)</td>\n",
       "      <td>140.6 (15.5)</td>\n",
       "      <td>141.9 (15.8)</td>\n",
       "      <td>139.3 (15.3)</td>\n",
       "      <td>631</td>\n",
       "      <td>141.2 (15.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>红细胞压积</th>\n",
       "      <td>43.7 (4.3)</td>\n",
       "      <td>43.1 (4.2)</td>\n",
       "      <td>43.5 (4.4)</td>\n",
       "      <td>42.0 (4.0)</td>\n",
       "      <td>41.7 (4.1)</td>\n",
       "      <td>41.7 (4.0)</td>\n",
       "      <td>42.4 (4.1)</td>\n",
       "      <td>42.6 (4.2)</td>\n",
       "      <td>42.4 (4.2)</td>\n",
       "      <td>630</td>\n",
       "      <td>42.6 (4.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均红细胞体积</th>\n",
       "      <td>90.5 (5.1)</td>\n",
       "      <td>90.4 (5.1)</td>\n",
       "      <td>90.7 (5.2)</td>\n",
       "      <td>90.1 (5.3)</td>\n",
       "      <td>90.0 (5.3)</td>\n",
       "      <td>90.6 (5.3)</td>\n",
       "      <td>90.4 (5.1)</td>\n",
       "      <td>90.3 (5.0)</td>\n",
       "      <td>90.7 (5.1)</td>\n",
       "      <td>630</td>\n",
       "      <td>90.4 (5.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均血红蛋白含量</th>\n",
       "      <td>30.1 (2.1)</td>\n",
       "      <td>30.1 (2.1)</td>\n",
       "      <td>30.0 (2.1)</td>\n",
       "      <td>29.9 (2.2)</td>\n",
       "      <td>29.9 (2.3)</td>\n",
       "      <td>29.7 (2.2)</td>\n",
       "      <td>29.9 (2.1)</td>\n",
       "      <td>30.1 (2.1)</td>\n",
       "      <td>29.8 (2.1)</td>\n",
       "      <td>630</td>\n",
       "      <td>30.0 (2.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均血红蛋白浓度</th>\n",
       "      <td>333.0 (10.7)</td>\n",
       "      <td>333.1 (10.7)</td>\n",
       "      <td>330.2 (10.4)</td>\n",
       "      <td>331.6 (12.0)</td>\n",
       "      <td>331.6 (11.3)</td>\n",
       "      <td>327.5 (10.2)</td>\n",
       "      <td>331.1 (11.4)</td>\n",
       "      <td>332.9 (10.9)</td>\n",
       "      <td>328.4 (10.0)</td>\n",
       "      <td>630</td>\n",
       "      <td>331.2 (11.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>红细胞分布宽度</th>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>12.6 (1.2)</td>\n",
       "      <td>12.7 (1.2)</td>\n",
       "      <td>12.9 (1.2)</td>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.5 (1.0)</td>\n",
       "      <td>12.9 (1.1)</td>\n",
       "      <td>632</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均血小板体积</th>\n",
       "      <td>10.7 (1.0)</td>\n",
       "      <td>10.6 (1.0)</td>\n",
       "      <td>10.4 (1.0)</td>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.5 (1.1)</td>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.7 (1.0)</td>\n",
       "      <td>10.6 (1.0)</td>\n",
       "      <td>972</td>\n",
       "      <td>10.7 (1.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血小板压积</th>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>972</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性粒细胞</th>\n",
       "      <td>3.6 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.6 (1.3)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>630</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>淋巴细胞</th>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.0 (0.6)</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>630</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>单核细胞</th>\n",
       "      <td>0.5 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>630</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜酸性粒细胞</th>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.2 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>630</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜碱性粒细胞</th>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>630</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>谷丙转氨酶</th>\n",
       "      <td>22.3 (20.1)</td>\n",
       "      <td>22.5 (19.0)</td>\n",
       "      <td>23.3 (23.0)</td>\n",
       "      <td>18.6 (16.2)</td>\n",
       "      <td>18.9 (16.6)</td>\n",
       "      <td>21.1 (20.3)</td>\n",
       "      <td>19.5 (26.5)</td>\n",
       "      <td>22.3 (20.4)</td>\n",
       "      <td>20.7 (18.3)</td>\n",
       "      <td>602</td>\n",
       "      <td>20.9 (19.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>谷草转氨酶</th>\n",
       "      <td>20.6 (10.5)</td>\n",
       "      <td>20.1 (8.5)</td>\n",
       "      <td>20.6 (11.5)</td>\n",
       "      <td>19.8 (7.9)</td>\n",
       "      <td>20.7 (11.2)</td>\n",
       "      <td>20.5 (9.2)</td>\n",
       "      <td>20.9 (21.1)</td>\n",
       "      <td>21.3 (9.5)</td>\n",
       "      <td>21.1 (11.1)</td>\n",
       "      <td>21396</td>\n",
       "      <td>20.6 (11.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>碱性磷酸酶</th>\n",
       "      <td>70.6 (21.7)</td>\n",
       "      <td>71.6 (21.9)</td>\n",
       "      <td>71.1 (21.0)</td>\n",
       "      <td>67.1 (20.5)</td>\n",
       "      <td>64.8 (18.2)</td>\n",
       "      <td>67.4 (20.3)</td>\n",
       "      <td>66.9 (21.7)</td>\n",
       "      <td>68.8 (20.7)</td>\n",
       "      <td>66.4 (20.2)</td>\n",
       "      <td>758</td>\n",
       "      <td>68.2 (20.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>腺苷酸脱氨酶</th>\n",
       "      <td>8.7 (2.2)</td>\n",
       "      <td>8.4 (2.2)</td>\n",
       "      <td>8.8 (2.2)</td>\n",
       "      <td>8.9 (2.4)</td>\n",
       "      <td>8.5 (2.2)</td>\n",
       "      <td>8.9 (2.4)</td>\n",
       "      <td>8.7 (2.5)</td>\n",
       "      <td>8.6 (2.4)</td>\n",
       "      <td>9.0 (2.7)</td>\n",
       "      <td>25322</td>\n",
       "      <td>8.7 (2.3)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甘脯二肽氨基肽酶</th>\n",
       "      <td>79.2 (18.4)</td>\n",
       "      <td>81.2 (18.2)</td>\n",
       "      <td>80.5 (18.7)</td>\n",
       "      <td>77.6 (18.3)</td>\n",
       "      <td>79.0 (17.9)</td>\n",
       "      <td>73.8 (17.4)</td>\n",
       "      <td>77.1 (17.5)</td>\n",
       "      <td>82.8 (20.2)</td>\n",
       "      <td>77.7 (18.6)</td>\n",
       "      <td>23421</td>\n",
       "      <td>79.2 (18.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>α-岩藻糖苷酶</th>\n",
       "      <td>20.5 (5.4)</td>\n",
       "      <td>20.6 (5.3)</td>\n",
       "      <td>21.5 (5.5)</td>\n",
       "      <td>20.3 (5.0)</td>\n",
       "      <td>20.6 (5.1)</td>\n",
       "      <td>21.6 (5.6)</td>\n",
       "      <td>20.6 (5.4)</td>\n",
       "      <td>20.8 (5.1)</td>\n",
       "      <td>22.0 (5.6)</td>\n",
       "      <td>25322</td>\n",
       "      <td>20.9 (5.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>三碘甲腺原氨酸</th>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.5 (0.2)</td>\n",
       "      <td>1.6 (0.2)</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.5 (0.2)</td>\n",
       "      <td>1.6 (0.4)</td>\n",
       "      <td>1.5 (0.6)</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.6 (0.3)</td>\n",
       "      <td>26889</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>四碘甲状腺原氨酸</th>\n",
       "      <td>97.7 (16.6)</td>\n",
       "      <td>99.9 (16.7)</td>\n",
       "      <td>101.3 (16.0)</td>\n",
       "      <td>99.9 (16.6)</td>\n",
       "      <td>97.6 (15.9)</td>\n",
       "      <td>101.3 (17.5)</td>\n",
       "      <td>98.2 (17.5)</td>\n",
       "      <td>98.1 (16.9)</td>\n",
       "      <td>96.6 (17.2)</td>\n",
       "      <td>17170</td>\n",
       "      <td>98.8 (16.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>促甲状腺素</th>\n",
       "      <td>2.0 (3.4)</td>\n",
       "      <td>1.9 (1.4)</td>\n",
       "      <td>1.8 (1.2)</td>\n",
       "      <td>1.9 (2.9)</td>\n",
       "      <td>1.8 (2.1)</td>\n",
       "      <td>1.8 (1.2)</td>\n",
       "      <td>1.9 (1.5)</td>\n",
       "      <td>1.8 (1.2)</td>\n",
       "      <td>2.0 (5.8)</td>\n",
       "      <td>17170</td>\n",
       "      <td>1.9 (2.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>游离甲状腺素</th>\n",
       "      <td>13.8 (1.7)</td>\n",
       "      <td>13.5 (1.5)</td>\n",
       "      <td>14.0 (1.5)</td>\n",
       "      <td>13.4 (1.6)</td>\n",
       "      <td>13.3 (1.5)</td>\n",
       "      <td>13.5 (1.9)</td>\n",
       "      <td>13.1 (1.5)</td>\n",
       "      <td>13.4 (1.5)</td>\n",
       "      <td>13.6 (1.8)</td>\n",
       "      <td>25648</td>\n",
       "      <td>13.5 (1.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甲状腺过氧化物酶抗体</th>\n",
       "      <td>22.6 (110.2)</td>\n",
       "      <td>26.6 (126.5)</td>\n",
       "      <td>27.5 (128.1)</td>\n",
       "      <td>37.7 (153.8)</td>\n",
       "      <td>36.2 (144.7)</td>\n",
       "      <td>26.5 (107.1)</td>\n",
       "      <td>41.1 (154.0)</td>\n",
       "      <td>34.2 (142.1)</td>\n",
       "      <td>43.8 (168.2)</td>\n",
       "      <td>29400</td>\n",
       "      <td>32.0 (137.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总胆红素</th>\n",
       "      <td>11.8 (5.5)</td>\n",
       "      <td>11.7 (5.3)</td>\n",
       "      <td>11.7 (5.5)</td>\n",
       "      <td>11.0 (4.9)</td>\n",
       "      <td>11.0 (5.0)</td>\n",
       "      <td>11.0 (4.8)</td>\n",
       "      <td>11.1 (5.0)</td>\n",
       "      <td>10.9 (5.0)</td>\n",
       "      <td>10.9 (4.8)</td>\n",
       "      <td>602</td>\n",
       "      <td>11.2 (5.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>直接胆红素</th>\n",
       "      <td>4.0 (1.6)</td>\n",
       "      <td>4.1 (1.6)</td>\n",
       "      <td>4.2 (1.9)</td>\n",
       "      <td>3.8 (1.4)</td>\n",
       "      <td>4.0 (1.5)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>603</td>\n",
       "      <td>4.0 (1.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>间接胆红素</th>\n",
       "      <td>7.8 (4.1)</td>\n",
       "      <td>7.6 (3.9)</td>\n",
       "      <td>7.5 (3.9)</td>\n",
       "      <td>7.1 (3.6)</td>\n",
       "      <td>7.0 (3.6)</td>\n",
       "      <td>7.1 (3.5)</td>\n",
       "      <td>7.2 (3.6)</td>\n",
       "      <td>7.0 (3.6)</td>\n",
       "      <td>7.0 (3.5)</td>\n",
       "      <td>608</td>\n",
       "      <td>7.3 (3.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总胆汁酸</th>\n",
       "      <td>4.8 (7.8)</td>\n",
       "      <td>4.7 (3.9)</td>\n",
       "      <td>5.0 (3.8)</td>\n",
       "      <td>4.8 (5.4)</td>\n",
       "      <td>4.8 (4.4)</td>\n",
       "      <td>4.9 (3.9)</td>\n",
       "      <td>4.6 (3.7)</td>\n",
       "      <td>4.9 (3.8)</td>\n",
       "      <td>5.2 (4.7)</td>\n",
       "      <td>23423</td>\n",
       "      <td>4.8 (5.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>肌酐</th>\n",
       "      <td>73.7 (17.1)</td>\n",
       "      <td>70.7 (15.8)</td>\n",
       "      <td>71.6 (18.3)</td>\n",
       "      <td>68.3 (14.4)</td>\n",
       "      <td>65.6 (14.5)</td>\n",
       "      <td>64.6 (15.8)</td>\n",
       "      <td>66.5 (20.6)</td>\n",
       "      <td>68.2 (21.0)</td>\n",
       "      <td>66.6 (17.5)</td>\n",
       "      <td>660</td>\n",
       "      <td>68.7 (17.3)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2020-12       2021-12       2022-12       2021-01  \\\n",
       "item_name                                                            \n",
       "心率           83.7 (13.4)   84.4 (13.1)   85.6 (13.3)   84.9 (13.0)   \n",
       "同型半胱氨酸        11.9 (6.7)     9.9 (4.6)    10.1 (4.3)     9.0 (4.5)   \n",
       "收缩压         123.9 (16.5)  124.5 (17.0)  124.0 (17.0)  121.1 (15.7)   \n",
       "舒张压          74.0 (10.7)   73.8 (10.9)   73.7 (10.8)   71.2 (10.2)   \n",
       "甘油三酯           1.4 (1.3)     1.4 (1.0)     1.4 (1.1)     1.1 (0.9)   \n",
       "总胆固醇           4.6 (0.9)     4.8 (0.9)     4.8 (1.0)     4.5 (0.9)   \n",
       "高密度脂蛋白         1.3 (0.3)     1.4 (0.4)     1.4 (0.4)     1.4 (0.4)   \n",
       "低密度脂蛋白         2.6 (0.7)     2.7 (0.8)     2.8 (0.8)     2.5 (0.7)   \n",
       "空腹血糖           5.1 (1.0)     5.0 (1.1)     5.0 (1.0)     4.9 (0.8)   \n",
       "糖化血红蛋白A1       7.0 (0.8)     6.9 (0.8)     6.9 (0.8)     6.8 (0.7)   \n",
       "糖化血红蛋白A1c      5.8 (0.7)     5.7 (0.8)     5.7 (0.7)     5.6 (0.6)   \n",
       "中性粒细胞(%)      55.7 (8.3)    55.3 (8.2)    55.5 (8.4)    55.5 (8.5)   \n",
       "淋巴细胞(%)       34.0 (7.7)    34.7 (7.7)    34.8 (7.9)    34.6 (7.9)   \n",
       "单核细胞(%)        7.3 (1.7)     7.0 (1.6)     6.7 (1.8)     7.1 (1.7)   \n",
       "嗜碱性粒细胞(%)      0.6 (0.3)     0.6 (0.3)     0.6 (0.3)     0.6 (0.3)   \n",
       "嗜酸性粒细胞(%)      2.3 (1.9)     2.4 (1.9)     2.4 (1.8)     2.1 (1.6)   \n",
       "红细胞计数          4.8 (0.5)     4.8 (0.5)     4.8 (0.5)     4.7 (0.5)   \n",
       "血小板计数       246.9 (57.3)  249.9 (57.8)  252.7 (57.4)  247.2 (57.0)   \n",
       "白细胞计数          6.3 (1.6)     6.1 (1.6)     6.4 (1.6)     6.0 (1.5)   \n",
       "血红蛋白        145.5 (16.3)  143.8 (16.1)  143.8 (16.2)  139.5 (15.3)   \n",
       "红细胞压积         43.7 (4.3)    43.1 (4.2)    43.5 (4.4)    42.0 (4.0)   \n",
       "平均红细胞体积       90.5 (5.1)    90.4 (5.1)    90.7 (5.2)    90.1 (5.3)   \n",
       "平均血红蛋白含量      30.1 (2.1)    30.1 (2.1)    30.0 (2.1)    29.9 (2.2)   \n",
       "平均血红蛋白浓度    333.0 (10.7)  333.1 (10.7)  330.2 (10.4)  331.6 (12.0)   \n",
       "红细胞分布宽度       12.6 (1.1)    12.7 (1.1)    12.7 (1.1)    12.6 (1.2)   \n",
       "平均血小板体积       10.7 (1.0)    10.6 (1.0)    10.4 (1.0)    10.8 (1.0)   \n",
       "血小板压积          0.3 (0.1)     0.3 (0.1)     0.3 (0.1)     0.3 (0.1)   \n",
       "中性粒细胞          3.6 (1.2)     3.4 (1.2)     3.6 (1.3)     3.4 (1.2)   \n",
       "淋巴细胞           2.1 (0.6)     2.1 (0.6)     2.2 (0.6)     2.0 (0.6)   \n",
       "单核细胞           0.5 (0.1)     0.4 (0.1)     0.4 (0.1)     0.4 (0.1)   \n",
       "嗜酸性粒细胞         0.1 (0.1)     0.1 (0.1)     0.2 (0.1)     0.1 (0.1)   \n",
       "嗜碱性粒细胞         0.0 (0.0)     0.0 (0.0)     0.0 (0.0)     0.0 (0.0)   \n",
       "谷丙转氨酶        22.3 (20.1)   22.5 (19.0)   23.3 (23.0)   18.6 (16.2)   \n",
       "谷草转氨酶        20.6 (10.5)    20.1 (8.5)   20.6 (11.5)    19.8 (7.9)   \n",
       "碱性磷酸酶        70.6 (21.7)   71.6 (21.9)   71.1 (21.0)   67.1 (20.5)   \n",
       "腺苷酸脱氨酶         8.7 (2.2)     8.4 (2.2)     8.8 (2.2)     8.9 (2.4)   \n",
       "甘脯二肽氨基肽酶     79.2 (18.4)   81.2 (18.2)   80.5 (18.7)   77.6 (18.3)   \n",
       "α-岩藻糖苷酶       20.5 (5.4)    20.6 (5.3)    21.5 (5.5)    20.3 (5.0)   \n",
       "三碘甲腺原氨酸        1.5 (0.3)     1.5 (0.2)     1.6 (0.2)     1.5 (0.3)   \n",
       "四碘甲状腺原氨酸     97.7 (16.6)   99.9 (16.7)  101.3 (16.0)   99.9 (16.6)   \n",
       "促甲状腺素          2.0 (3.4)     1.9 (1.4)     1.8 (1.2)     1.9 (2.9)   \n",
       "游离甲状腺素        13.8 (1.7)    13.5 (1.5)    14.0 (1.5)    13.4 (1.6)   \n",
       "甲状腺过氧化物酶抗体  22.6 (110.2)  26.6 (126.5)  27.5 (128.1)  37.7 (153.8)   \n",
       "总胆红素          11.8 (5.5)    11.7 (5.3)    11.7 (5.5)    11.0 (4.9)   \n",
       "直接胆红素          4.0 (1.6)     4.1 (1.6)     4.2 (1.9)     3.8 (1.4)   \n",
       "间接胆红素          7.8 (4.1)     7.6 (3.9)     7.5 (3.9)     7.1 (3.6)   \n",
       "总胆汁酸           4.8 (7.8)     4.7 (3.9)     5.0 (3.8)     4.8 (5.4)   \n",
       "肌酐           73.7 (17.1)   70.7 (15.8)   71.6 (18.3)   68.3 (14.4)   \n",
       "\n",
       "                 2022-01       2023-01       2021-02       2022-02  \\\n",
       "item_name                                                            \n",
       "心率           84.8 (12.4)   86.8 (13.2)   84.3 (12.9)   85.3 (12.4)   \n",
       "同型半胱氨酸         9.2 (4.0)     9.7 (2.9)     8.2 (3.9)     9.1 (3.7)   \n",
       "收缩压         119.7 (14.6)  122.1 (14.4)  120.5 (16.3)  121.3 (15.6)   \n",
       "舒张压          71.4 (10.0)    73.9 (9.6)   71.2 (10.4)   72.5 (10.5)   \n",
       "甘油三酯           1.1 (0.9)     1.2 (0.9)     1.2 (1.0)     1.3 (1.1)   \n",
       "总胆固醇           4.7 (0.9)     4.7 (0.9)     4.5 (0.9)     4.8 (0.9)   \n",
       "高密度脂蛋白         1.5 (0.4)     1.4 (0.3)     1.4 (0.4)     1.4 (0.4)   \n",
       "低密度脂蛋白         2.5 (0.7)     2.6 (0.7)     2.5 (0.7)     2.7 (0.7)   \n",
       "空腹血糖           4.8 (0.7)     4.9 (0.8)     4.8 (0.8)     5.0 (0.9)   \n",
       "糖化血红蛋白A1       6.9 (0.8)     7.0 (0.9)     6.8 (0.6)     6.9 (0.8)   \n",
       "糖化血红蛋白A1c      5.7 (0.7)     5.8 (0.8)     5.6 (0.5)     5.7 (0.7)   \n",
       "中性粒细胞(%)      54.5 (8.7)    55.5 (8.5)    55.1 (8.4)    54.5 (8.4)   \n",
       "淋巴细胞(%)       35.8 (8.1)    35.0 (7.8)    35.1 (7.9)    35.7 (7.9)   \n",
       "单核细胞(%)        7.1 (1.6)     6.9 (1.7)     7.1 (1.6)     7.0 (1.6)   \n",
       "嗜碱性粒细胞(%)      0.6 (0.3)     0.5 (0.3)     0.6 (0.3)     0.6 (0.3)   \n",
       "嗜酸性粒细胞(%)      2.1 (1.6)     2.1 (1.6)     2.2 (1.7)     2.2 (1.7)   \n",
       "红细胞计数          4.6 (0.5)     4.6 (0.5)     4.7 (0.5)     4.7 (0.5)   \n",
       "血小板计数       251.0 (57.7)  256.0 (63.3)  243.5 (57.5)  250.2 (56.6)   \n",
       "白细胞计数          6.1 (1.6)     6.1 (1.5)     6.0 (1.5)     6.2 (1.6)   \n",
       "血红蛋白        138.3 (15.6)  136.5 (14.7)  140.6 (15.5)  141.9 (15.8)   \n",
       "红细胞压积         41.7 (4.1)    41.7 (4.0)    42.4 (4.1)    42.6 (4.2)   \n",
       "平均红细胞体积       90.0 (5.3)    90.6 (5.3)    90.4 (5.1)    90.3 (5.0)   \n",
       "平均血红蛋白含量      29.9 (2.3)    29.7 (2.2)    29.9 (2.1)    30.1 (2.1)   \n",
       "平均血红蛋白浓度    331.6 (11.3)  327.5 (10.2)  331.1 (11.4)  332.9 (10.9)   \n",
       "红细胞分布宽度       12.7 (1.2)    12.9 (1.2)    12.6 (1.1)    12.5 (1.0)   \n",
       "平均血小板体积       10.8 (1.0)    10.5 (1.1)    10.8 (1.0)    10.7 (1.0)   \n",
       "血小板压积          0.3 (0.1)     0.3 (0.1)     0.3 (0.1)     0.3 (0.1)   \n",
       "中性粒细胞          3.4 (1.2)     3.4 (1.2)     3.4 (1.2)     3.4 (1.2)   \n",
       "淋巴细胞           2.1 (0.6)     2.1 (0.6)     2.1 (0.6)     2.2 (0.6)   \n",
       "单核细胞           0.4 (0.1)     0.4 (0.1)     0.4 (0.1)     0.4 (0.1)   \n",
       "嗜酸性粒细胞         0.1 (0.1)     0.1 (0.1)     0.1 (0.1)     0.1 (0.1)   \n",
       "嗜碱性粒细胞         0.0 (0.0)     0.0 (0.0)     0.0 (0.0)     0.0 (0.0)   \n",
       "谷丙转氨酶        18.9 (16.6)   21.1 (20.3)   19.5 (26.5)   22.3 (20.4)   \n",
       "谷草转氨酶        20.7 (11.2)    20.5 (9.2)   20.9 (21.1)    21.3 (9.5)   \n",
       "碱性磷酸酶        64.8 (18.2)   67.4 (20.3)   66.9 (21.7)   68.8 (20.7)   \n",
       "腺苷酸脱氨酶         8.5 (2.2)     8.9 (2.4)     8.7 (2.5)     8.6 (2.4)   \n",
       "甘脯二肽氨基肽酶     79.0 (17.9)   73.8 (17.4)   77.1 (17.5)   82.8 (20.2)   \n",
       "α-岩藻糖苷酶       20.6 (5.1)    21.6 (5.6)    20.6 (5.4)    20.8 (5.1)   \n",
       "三碘甲腺原氨酸        1.5 (0.2)     1.6 (0.4)     1.5 (0.6)     1.5 (0.3)   \n",
       "四碘甲状腺原氨酸     97.6 (15.9)  101.3 (17.5)   98.2 (17.5)   98.1 (16.9)   \n",
       "促甲状腺素          1.8 (2.1)     1.8 (1.2)     1.9 (1.5)     1.8 (1.2)   \n",
       "游离甲状腺素        13.3 (1.5)    13.5 (1.9)    13.1 (1.5)    13.4 (1.5)   \n",
       "甲状腺过氧化物酶抗体  36.2 (144.7)  26.5 (107.1)  41.1 (154.0)  34.2 (142.1)   \n",
       "总胆红素          11.0 (5.0)    11.0 (4.8)    11.1 (5.0)    10.9 (5.0)   \n",
       "直接胆红素          4.0 (1.5)     3.9 (1.5)     3.9 (1.5)     3.9 (1.5)   \n",
       "间接胆红素          7.0 (3.6)     7.1 (3.5)     7.2 (3.6)     7.0 (3.6)   \n",
       "总胆汁酸           4.8 (4.4)     4.9 (3.9)     4.6 (3.7)     4.9 (3.8)   \n",
       "肌酐           65.6 (14.5)   64.6 (15.8)   66.5 (20.6)   68.2 (21.0)   \n",
       "\n",
       "                 2023-02  Missing       Overall  \n",
       "item_name                                        \n",
       "心率           85.0 (12.2)     4569   84.8 (12.9)  \n",
       "同型半胱氨酸        10.3 (4.2)    28513     9.6 (4.9)  \n",
       "收缩压         121.8 (15.6)     4574  122.1 (16.0)  \n",
       "舒张压          72.8 (10.3)     4571   72.7 (10.5)  \n",
       "甘油三酯           1.3 (1.2)     2516     1.3 (1.1)  \n",
       "总胆固醇           4.8 (0.9)     2517     4.7 (0.9)  \n",
       "高密度脂蛋白         1.4 (0.4)     2518     1.4 (0.4)  \n",
       "低密度脂蛋白         2.6 (0.7)     2518     2.6 (0.7)  \n",
       "空腹血糖           4.9 (1.0)      668     4.9 (0.9)  \n",
       "糖化血红蛋白A1       7.0 (0.9)    22037     6.9 (0.8)  \n",
       "糖化血红蛋白A1c      5.8 (0.8)    22037     5.7 (0.7)  \n",
       "中性粒细胞(%)      54.8 (8.1)      630    55.2 (8.4)  \n",
       "淋巴细胞(%)       35.6 (7.6)      630    35.0 (7.9)  \n",
       "单核细胞(%)        6.8 (1.6)      630     7.0 (1.7)  \n",
       "嗜碱性粒细胞(%)      0.6 (0.3)      630     0.6 (0.3)  \n",
       "嗜酸性粒细胞(%)      2.3 (1.8)      630     2.2 (1.8)  \n",
       "红细胞计数          4.7 (0.5)      630     4.7 (0.5)  \n",
       "血小板计数       253.5 (58.0)      634  249.9 (57.9)  \n",
       "白细胞计数          6.2 (1.6)      631     6.2 (1.6)  \n",
       "血红蛋白        139.3 (15.3)      631  141.2 (15.9)  \n",
       "红细胞压积         42.4 (4.2)      630    42.6 (4.2)  \n",
       "平均红细胞体积       90.7 (5.1)      630    90.4 (5.2)  \n",
       "平均血红蛋白含量      29.8 (2.1)      630    30.0 (2.2)  \n",
       "平均血红蛋白浓度    328.4 (10.0)      630  331.2 (11.0)  \n",
       "红细胞分布宽度       12.9 (1.1)      632    12.7 (1.1)  \n",
       "平均血小板体积       10.6 (1.0)      972    10.7 (1.0)  \n",
       "血小板压积          0.3 (0.1)      972     0.3 (0.1)  \n",
       "中性粒细胞          3.4 (1.2)      630     3.4 (1.2)  \n",
       "淋巴细胞           2.2 (0.6)      630     2.1 (0.6)  \n",
       "单核细胞           0.4 (0.1)      630     0.4 (0.1)  \n",
       "嗜酸性粒细胞         0.1 (0.1)      630     0.1 (0.1)  \n",
       "嗜碱性粒细胞         0.0 (0.0)      630     0.0 (0.0)  \n",
       "谷丙转氨酶        20.7 (18.3)      602   20.9 (19.8)  \n",
       "谷草转氨酶        21.1 (11.1)    21396   20.6 (11.0)  \n",
       "碱性磷酸酶        66.4 (20.2)      758   68.2 (20.8)  \n",
       "腺苷酸脱氨酶         9.0 (2.7)    25322     8.7 (2.3)  \n",
       "甘脯二肽氨基肽酶     77.7 (18.6)    23421   79.2 (18.5)  \n",
       "α-岩藻糖苷酶       22.0 (5.6)    25322    20.9 (5.4)  \n",
       "三碘甲腺原氨酸        1.6 (0.3)    26889     1.5 (0.3)  \n",
       "四碘甲状腺原氨酸     96.6 (17.2)    17170   98.8 (16.8)  \n",
       "促甲状腺素          2.0 (5.8)    17170     1.9 (2.9)  \n",
       "游离甲状腺素        13.6 (1.8)    25648    13.5 (1.6)  \n",
       "甲状腺过氧化物酶抗体  43.8 (168.2)    29400  32.0 (137.9)  \n",
       "总胆红素          10.9 (4.8)      602    11.2 (5.1)  \n",
       "直接胆红素          3.9 (1.5)      603     4.0 (1.6)  \n",
       "间接胆红素          7.0 (3.5)      608     7.3 (3.7)  \n",
       "总胆汁酸           5.2 (4.7)    23423     4.8 (5.4)  \n",
       "肌酐           66.6 (17.5)      660   68.7 (17.3)  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_order = ['2020-12', '2021-12', '2022-12', \n",
    "             '2021-01', '2022-01', '2023-01', \n",
    "             '2021-02', '2022-02', '2023-02', 'Missing', 'Overall']\n",
    "\n",
    "def show_cont_table(my_table_value):\n",
    "    my_table_value = mytable.cont_table\n",
    "    my_table_value.loc[l_columns].columns\n",
    "    my_table_value = my_table_value.loc[l_columns, col_order]\n",
    "    my_table_value.index = df_meta_groups.loc[l_columns][\"item_name\"]\n",
    "    return my_table_value\n",
    "\n",
    "mytable = tableone.TableOne(df_table1plus[df_table1plus[\"month\"].isin([12,1,2])], l_columns, [], \"year-month\")\n",
    "show_cont_table(mytable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3c3ef142",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2020-12</th>\n",
       "      <th>2021-12</th>\n",
       "      <th>2022-12</th>\n",
       "      <th>2021-01</th>\n",
       "      <th>2022-01</th>\n",
       "      <th>2023-01</th>\n",
       "      <th>2021-02</th>\n",
       "      <th>2022-02</th>\n",
       "      <th>2023-02</th>\n",
       "      <th>Missing</th>\n",
       "      <th>Overall</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>item_name</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>心率</th>\n",
       "      <td>84.3 (13.1)</td>\n",
       "      <td>84.8 (13.0)</td>\n",
       "      <td>86.1 (13.1)</td>\n",
       "      <td>85.4 (12.7)</td>\n",
       "      <td>84.7 (11.8)</td>\n",
       "      <td>86.5 (12.0)</td>\n",
       "      <td>86.0 (12.8)</td>\n",
       "      <td>85.5 (12.3)</td>\n",
       "      <td>85.4 (12.0)</td>\n",
       "      <td>1630</td>\n",
       "      <td>85.5 (12.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>同型半胱氨酸</th>\n",
       "      <td>10.9 (5.1)</td>\n",
       "      <td>9.7 (3.9)</td>\n",
       "      <td>10.0 (3.5)</td>\n",
       "      <td>8.0 (3.7)</td>\n",
       "      <td>8.2 (3.2)</td>\n",
       "      <td>8.9 (2.5)</td>\n",
       "      <td>8.7 (4.2)</td>\n",
       "      <td>9.0 (3.5)</td>\n",
       "      <td>10.2 (4.7)</td>\n",
       "      <td>14200</td>\n",
       "      <td>8.9 (4.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>收缩压</th>\n",
       "      <td>127.2 (18.8)</td>\n",
       "      <td>125.8 (18.3)</td>\n",
       "      <td>127.7 (19.2)</td>\n",
       "      <td>119.4 (14.8)</td>\n",
       "      <td>119.5 (14.8)</td>\n",
       "      <td>121.7 (14.2)</td>\n",
       "      <td>120.0 (14.8)</td>\n",
       "      <td>119.9 (14.7)</td>\n",
       "      <td>120.9 (15.1)</td>\n",
       "      <td>1631</td>\n",
       "      <td>121.2 (15.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>舒张压</th>\n",
       "      <td>74.4 (11.0)</td>\n",
       "      <td>73.5 (10.7)</td>\n",
       "      <td>74.6 (10.8)</td>\n",
       "      <td>71.1 (10.1)</td>\n",
       "      <td>71.4 (9.8)</td>\n",
       "      <td>73.8 (9.5)</td>\n",
       "      <td>71.1 (9.8)</td>\n",
       "      <td>71.3 (9.7)</td>\n",
       "      <td>72.1 (9.9)</td>\n",
       "      <td>1629</td>\n",
       "      <td>72.0 (10.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甘油三酯</th>\n",
       "      <td>1.4 (1.1)</td>\n",
       "      <td>1.4 (1.4)</td>\n",
       "      <td>1.4 (0.7)</td>\n",
       "      <td>1.1 (0.8)</td>\n",
       "      <td>1.1 (0.8)</td>\n",
       "      <td>1.2 (0.8)</td>\n",
       "      <td>1.1 (0.9)</td>\n",
       "      <td>1.2 (1.1)</td>\n",
       "      <td>1.2 (0.9)</td>\n",
       "      <td>218</td>\n",
       "      <td>1.2 (1.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总胆固醇</th>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.9 (0.9)</td>\n",
       "      <td>4.9 (1.0)</td>\n",
       "      <td>4.5 (0.8)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.4 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>218</td>\n",
       "      <td>4.6 (0.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>高密度脂蛋白</th>\n",
       "      <td>1.3 (0.3)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.3)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>1.4 (0.3)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>218</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>低密度脂蛋白</th>\n",
       "      <td>2.7 (0.7)</td>\n",
       "      <td>2.7 (0.8)</td>\n",
       "      <td>2.8 (0.8)</td>\n",
       "      <td>2.4 (0.7)</td>\n",
       "      <td>2.5 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2.4 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>218</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>空腹血糖</th>\n",
       "      <td>5.2 (1.1)</td>\n",
       "      <td>5.1 (1.1)</td>\n",
       "      <td>5.1 (1.3)</td>\n",
       "      <td>4.9 (0.7)</td>\n",
       "      <td>4.8 (0.7)</td>\n",
       "      <td>4.9 (0.7)</td>\n",
       "      <td>4.8 (0.7)</td>\n",
       "      <td>4.9 (0.7)</td>\n",
       "      <td>4.8 (0.8)</td>\n",
       "      <td>67</td>\n",
       "      <td>4.9 (0.8)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>糖化血红蛋白A1</th>\n",
       "      <td>7.2 (0.8)</td>\n",
       "      <td>7.0 (0.9)</td>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>6.8 (0.6)</td>\n",
       "      <td>6.9 (0.7)</td>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>6.7 (0.6)</td>\n",
       "      <td>7.0 (0.9)</td>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>12224</td>\n",
       "      <td>6.9 (0.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>糖化血红蛋白A1c</th>\n",
       "      <td>5.9 (0.7)</td>\n",
       "      <td>5.8 (0.8)</td>\n",
       "      <td>5.8 (0.7)</td>\n",
       "      <td>5.6 (0.5)</td>\n",
       "      <td>5.7 (0.6)</td>\n",
       "      <td>5.8 (0.7)</td>\n",
       "      <td>5.6 (0.5)</td>\n",
       "      <td>5.7 (0.8)</td>\n",
       "      <td>5.8 (0.7)</td>\n",
       "      <td>12224</td>\n",
       "      <td>5.7 (0.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性粒细胞(%)</th>\n",
       "      <td>55.1 (8.2)</td>\n",
       "      <td>55.0 (8.2)</td>\n",
       "      <td>55.0 (8.3)</td>\n",
       "      <td>55.2 (8.8)</td>\n",
       "      <td>53.5 (8.5)</td>\n",
       "      <td>55.0 (8.5)</td>\n",
       "      <td>55.2 (8.5)</td>\n",
       "      <td>53.8 (8.5)</td>\n",
       "      <td>54.0 (8.0)</td>\n",
       "      <td>63</td>\n",
       "      <td>54.5 (8.4)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>淋巴细胞(%)</th>\n",
       "      <td>34.8 (7.6)</td>\n",
       "      <td>35.0 (7.6)</td>\n",
       "      <td>35.4 (8.0)</td>\n",
       "      <td>35.2 (8.1)</td>\n",
       "      <td>36.8 (8.0)</td>\n",
       "      <td>35.5 (7.9)</td>\n",
       "      <td>35.0 (7.9)</td>\n",
       "      <td>36.5 (8.0)</td>\n",
       "      <td>36.4 (7.6)</td>\n",
       "      <td>63</td>\n",
       "      <td>35.8 (7.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>单核细胞(%)</th>\n",
       "      <td>7.2 (1.7)</td>\n",
       "      <td>7.0 (1.7)</td>\n",
       "      <td>6.7 (1.8)</td>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>6.8 (1.6)</td>\n",
       "      <td>7.1 (1.7)</td>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>6.7 (1.6)</td>\n",
       "      <td>63</td>\n",
       "      <td>6.9 (1.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜碱性粒细胞(%)</th>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.5 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.5 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>63</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜酸性粒细胞(%)</th>\n",
       "      <td>2.3 (1.9)</td>\n",
       "      <td>2.4 (1.9)</td>\n",
       "      <td>2.4 (1.8)</td>\n",
       "      <td>2.1 (1.7)</td>\n",
       "      <td>2.2 (1.6)</td>\n",
       "      <td>2.2 (1.6)</td>\n",
       "      <td>2.1 (1.6)</td>\n",
       "      <td>2.2 (1.7)</td>\n",
       "      <td>2.3 (1.8)</td>\n",
       "      <td>63</td>\n",
       "      <td>2.2 (1.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>红细胞计数</th>\n",
       "      <td>4.8 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>63</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血小板计数</th>\n",
       "      <td>245.8 (59.0)</td>\n",
       "      <td>249.1 (58.5)</td>\n",
       "      <td>250.1 (59.2)</td>\n",
       "      <td>246.2 (58.3)</td>\n",
       "      <td>249.6 (57.3)</td>\n",
       "      <td>254.4 (63.6)</td>\n",
       "      <td>247.4 (56.3)</td>\n",
       "      <td>251.3 (57.0)</td>\n",
       "      <td>255.3 (57.3)</td>\n",
       "      <td>65</td>\n",
       "      <td>250.6 (58.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>白细胞计数</th>\n",
       "      <td>6.3 (1.5)</td>\n",
       "      <td>6.3 (1.6)</td>\n",
       "      <td>6.3 (1.6)</td>\n",
       "      <td>5.9 (1.5)</td>\n",
       "      <td>6.0 (1.5)</td>\n",
       "      <td>6.1 (1.5)</td>\n",
       "      <td>6.0 (1.5)</td>\n",
       "      <td>6.1 (1.5)</td>\n",
       "      <td>6.2 (1.6)</td>\n",
       "      <td>63</td>\n",
       "      <td>6.1 (1.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血红蛋白</th>\n",
       "      <td>144.1 (15.7)</td>\n",
       "      <td>143.3 (15.7)</td>\n",
       "      <td>142.2 (15.6)</td>\n",
       "      <td>138.0 (14.8)</td>\n",
       "      <td>137.8 (14.3)</td>\n",
       "      <td>135.4 (14.0)</td>\n",
       "      <td>138.9 (15.1)</td>\n",
       "      <td>137.9 (15.2)</td>\n",
       "      <td>137.2 (14.7)</td>\n",
       "      <td>63</td>\n",
       "      <td>138.6 (15.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>红细胞压积</th>\n",
       "      <td>43.2 (4.1)</td>\n",
       "      <td>43.0 (4.2)</td>\n",
       "      <td>43.2 (4.3)</td>\n",
       "      <td>41.7 (3.9)</td>\n",
       "      <td>41.6 (3.7)</td>\n",
       "      <td>41.3 (3.8)</td>\n",
       "      <td>41.9 (4.0)</td>\n",
       "      <td>41.6 (4.0)</td>\n",
       "      <td>41.8 (4.0)</td>\n",
       "      <td>63</td>\n",
       "      <td>41.9 (4.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均红细胞体积</th>\n",
       "      <td>90.6 (5.1)</td>\n",
       "      <td>90.7 (5.0)</td>\n",
       "      <td>91.3 (5.5)</td>\n",
       "      <td>90.2 (5.2)</td>\n",
       "      <td>90.4 (5.2)</td>\n",
       "      <td>90.8 (5.2)</td>\n",
       "      <td>90.0 (5.0)</td>\n",
       "      <td>90.1 (5.0)</td>\n",
       "      <td>90.6 (5.1)</td>\n",
       "      <td>63</td>\n",
       "      <td>90.4 (5.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均血红蛋白含量</th>\n",
       "      <td>30.2 (2.1)</td>\n",
       "      <td>30.2 (2.1)</td>\n",
       "      <td>30.0 (2.2)</td>\n",
       "      <td>29.9 (2.2)</td>\n",
       "      <td>29.9 (2.2)</td>\n",
       "      <td>29.7 (2.1)</td>\n",
       "      <td>29.8 (2.2)</td>\n",
       "      <td>29.9 (2.1)</td>\n",
       "      <td>29.7 (2.1)</td>\n",
       "      <td>63</td>\n",
       "      <td>29.9 (2.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均血红蛋白浓度</th>\n",
       "      <td>333.0 (10.9)</td>\n",
       "      <td>333.2 (10.4)</td>\n",
       "      <td>328.8 (10.1)</td>\n",
       "      <td>331.0 (11.6)</td>\n",
       "      <td>330.9 (10.8)</td>\n",
       "      <td>327.4 (10.0)</td>\n",
       "      <td>331.1 (11.5)</td>\n",
       "      <td>331.3 (10.9)</td>\n",
       "      <td>327.6 (9.8)</td>\n",
       "      <td>63</td>\n",
       "      <td>330.2 (10.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>红细胞分布宽度</th>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>12.8 (1.1)</td>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.9 (1.2)</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>13.0 (1.1)</td>\n",
       "      <td>64</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>平均血小板体积</th>\n",
       "      <td>10.7 (0.9)</td>\n",
       "      <td>10.6 (0.9)</td>\n",
       "      <td>10.3 (1.0)</td>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.5 (1.1)</td>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.7 (0.9)</td>\n",
       "      <td>10.6 (1.0)</td>\n",
       "      <td>218</td>\n",
       "      <td>10.7 (1.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血小板压积</th>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>218</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中性粒细胞</th>\n",
       "      <td>3.5 (1.2)</td>\n",
       "      <td>3.5 (1.2)</td>\n",
       "      <td>3.5 (1.2)</td>\n",
       "      <td>3.3 (1.2)</td>\n",
       "      <td>3.3 (1.1)</td>\n",
       "      <td>3.4 (1.1)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.3 (1.2)</td>\n",
       "      <td>3.4 (1.1)</td>\n",
       "      <td>63</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>淋巴细胞</th>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.2 (0.7)</td>\n",
       "      <td>2.0 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>63</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>单核细胞</th>\n",
       "      <td>0.5 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>63</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜酸性粒细胞</th>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>63</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>嗜碱性粒细胞</th>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>谷丙转氨酶</th>\n",
       "      <td>21.0 (17.4)</td>\n",
       "      <td>20.8 (16.5)</td>\n",
       "      <td>21.8 (20.0)</td>\n",
       "      <td>17.4 (13.6)</td>\n",
       "      <td>18.5 (18.3)</td>\n",
       "      <td>20.5 (19.1)</td>\n",
       "      <td>17.7 (17.9)</td>\n",
       "      <td>18.8 (15.7)</td>\n",
       "      <td>19.5 (17.2)</td>\n",
       "      <td>54</td>\n",
       "      <td>19.1 (17.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>谷草转氨酶</th>\n",
       "      <td>20.3 (10.2)</td>\n",
       "      <td>19.6 (8.8)</td>\n",
       "      <td>20.4 (9.7)</td>\n",
       "      <td>18.9 (7.6)</td>\n",
       "      <td>20.7 (9.9)</td>\n",
       "      <td>20.7 (9.0)</td>\n",
       "      <td>19.0 (11.7)</td>\n",
       "      <td>20.8 (10.6)</td>\n",
       "      <td>20.8 (7.8)</td>\n",
       "      <td>14606</td>\n",
       "      <td>20.0 (9.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>碱性磷酸酶</th>\n",
       "      <td>72.4 (20.6)</td>\n",
       "      <td>72.9 (21.3)</td>\n",
       "      <td>72.2 (20.7)</td>\n",
       "      <td>65.8 (19.0)</td>\n",
       "      <td>65.3 (19.3)</td>\n",
       "      <td>66.0 (19.3)</td>\n",
       "      <td>65.1 (18.7)</td>\n",
       "      <td>64.8 (18.4)</td>\n",
       "      <td>64.2 (18.2)</td>\n",
       "      <td>86</td>\n",
       "      <td>66.2 (19.2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>腺苷酸脱氨酶</th>\n",
       "      <td>8.5 (1.8)</td>\n",
       "      <td>8.3 (1.8)</td>\n",
       "      <td>8.8 (2.1)</td>\n",
       "      <td>8.1 (1.8)</td>\n",
       "      <td>7.8 (1.8)</td>\n",
       "      <td>8.5 (2.1)</td>\n",
       "      <td>8.7 (2.3)</td>\n",
       "      <td>8.4 (2.2)</td>\n",
       "      <td>8.8 (2.5)</td>\n",
       "      <td>15688</td>\n",
       "      <td>8.5 (2.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甘脯二肽氨基肽酶</th>\n",
       "      <td>77.5 (16.1)</td>\n",
       "      <td>80.1 (17.2)</td>\n",
       "      <td>79.2 (18.1)</td>\n",
       "      <td>74.4 (14.4)</td>\n",
       "      <td>78.3 (17.6)</td>\n",
       "      <td>72.2 (15.2)</td>\n",
       "      <td>75.5 (16.1)</td>\n",
       "      <td>79.1 (18.1)</td>\n",
       "      <td>75.7 (17.4)</td>\n",
       "      <td>14905</td>\n",
       "      <td>77.0 (16.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>α-岩藻糖苷酶</th>\n",
       "      <td>19.9 (4.9)</td>\n",
       "      <td>20.2 (4.8)</td>\n",
       "      <td>21.2 (5.2)</td>\n",
       "      <td>20.6 (4.8)</td>\n",
       "      <td>20.5 (4.8)</td>\n",
       "      <td>21.7 (5.1)</td>\n",
       "      <td>20.6 (5.0)</td>\n",
       "      <td>20.4 (4.9)</td>\n",
       "      <td>21.8 (5.3)</td>\n",
       "      <td>15688</td>\n",
       "      <td>20.8 (5.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>三碘甲腺原氨酸</th>\n",
       "      <td>1.5 (0.2)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>1.6 (0.2)</td>\n",
       "      <td>1.5 (0.2)</td>\n",
       "      <td>1.5 (0.2)</td>\n",
       "      <td>1.6 (0.4)</td>\n",
       "      <td>1.4 (0.3)</td>\n",
       "      <td>1.5 (0.2)</td>\n",
       "      <td>1.6 (0.3)</td>\n",
       "      <td>13513</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>四碘甲状腺原氨酸</th>\n",
       "      <td>100.1 (17.1)</td>\n",
       "      <td>100.9 (17.2)</td>\n",
       "      <td>102.7 (16.5)</td>\n",
       "      <td>100.2 (18.9)</td>\n",
       "      <td>98.9 (15.9)</td>\n",
       "      <td>102.5 (17.7)</td>\n",
       "      <td>98.8 (16.7)</td>\n",
       "      <td>97.8 (16.2)</td>\n",
       "      <td>97.2 (17.3)</td>\n",
       "      <td>9680</td>\n",
       "      <td>99.3 (17.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>促甲状腺素</th>\n",
       "      <td>2.0 (1.2)</td>\n",
       "      <td>2.0 (1.3)</td>\n",
       "      <td>2.0 (1.5)</td>\n",
       "      <td>1.9 (1.5)</td>\n",
       "      <td>1.9 (1.3)</td>\n",
       "      <td>1.8 (1.2)</td>\n",
       "      <td>1.9 (3.6)</td>\n",
       "      <td>1.8 (1.4)</td>\n",
       "      <td>2.2 (8.4)</td>\n",
       "      <td>9680</td>\n",
       "      <td>2.0 (3.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>游离甲状腺素</th>\n",
       "      <td>13.9 (1.5)</td>\n",
       "      <td>13.6 (1.5)</td>\n",
       "      <td>14.2 (1.6)</td>\n",
       "      <td>13.4 (1.7)</td>\n",
       "      <td>13.4 (1.6)</td>\n",
       "      <td>13.7 (2.2)</td>\n",
       "      <td>13.2 (1.5)</td>\n",
       "      <td>13.2 (1.6)</td>\n",
       "      <td>13.5 (1.8)</td>\n",
       "      <td>13774</td>\n",
       "      <td>13.5 (1.7)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>甲状腺过氧化物酶抗体</th>\n",
       "      <td>27.1 (134.4)</td>\n",
       "      <td>18.2 (100.9)</td>\n",
       "      <td>18.3 (97.9)</td>\n",
       "      <td>43.5 (155.5)</td>\n",
       "      <td>46.8 (142.4)</td>\n",
       "      <td>46.9 (145.7)</td>\n",
       "      <td>47.8 (166.6)</td>\n",
       "      <td>53.8 (174.5)</td>\n",
       "      <td>65.8 (205.9)</td>\n",
       "      <td>16210</td>\n",
       "      <td>41.3 (155.1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总胆红素</th>\n",
       "      <td>11.7 (5.0)</td>\n",
       "      <td>11.4 (5.0)</td>\n",
       "      <td>11.4 (5.0)</td>\n",
       "      <td>10.9 (5.0)</td>\n",
       "      <td>10.7 (4.8)</td>\n",
       "      <td>10.9 (4.7)</td>\n",
       "      <td>11.1 (5.0)</td>\n",
       "      <td>11.0 (5.1)</td>\n",
       "      <td>10.9 (4.8)</td>\n",
       "      <td>54</td>\n",
       "      <td>11.0 (4.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>直接胆红素</th>\n",
       "      <td>4.0 (1.5)</td>\n",
       "      <td>4.0 (1.5)</td>\n",
       "      <td>4.1 (1.5)</td>\n",
       "      <td>3.8 (1.5)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>3.9 (1.4)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>4.0 (1.6)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>54</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>间接胆红素</th>\n",
       "      <td>7.7 (3.7)</td>\n",
       "      <td>7.4 (3.6)</td>\n",
       "      <td>7.4 (3.6)</td>\n",
       "      <td>7.1 (3.7)</td>\n",
       "      <td>6.8 (3.4)</td>\n",
       "      <td>7.0 (3.4)</td>\n",
       "      <td>7.2 (3.6)</td>\n",
       "      <td>7.0 (3.7)</td>\n",
       "      <td>7.0 (3.4)</td>\n",
       "      <td>70</td>\n",
       "      <td>7.1 (3.6)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>总胆汁酸</th>\n",
       "      <td>4.7 (2.8)</td>\n",
       "      <td>4.9 (2.7)</td>\n",
       "      <td>5.1 (3.1)</td>\n",
       "      <td>4.4 (2.9)</td>\n",
       "      <td>4.6 (2.8)</td>\n",
       "      <td>5.1 (3.5)</td>\n",
       "      <td>5.2 (15.2)</td>\n",
       "      <td>5.5 (13.4)</td>\n",
       "      <td>5.6 (6.4)</td>\n",
       "      <td>14908</td>\n",
       "      <td>5.1 (8.9)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>肌酐</th>\n",
       "      <td>72.4 (21.0)</td>\n",
       "      <td>71.0 (23.3)</td>\n",
       "      <td>71.8 (25.4)</td>\n",
       "      <td>65.9 (14.4)</td>\n",
       "      <td>64.5 (15.3)</td>\n",
       "      <td>63.5 (16.3)</td>\n",
       "      <td>66.8 (19.2)</td>\n",
       "      <td>65.6 (19.3)</td>\n",
       "      <td>64.5 (17.4)</td>\n",
       "      <td>67</td>\n",
       "      <td>66.3 (18.8)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 2020-12       2021-12       2022-12       2021-01  \\\n",
       "item_name                                                            \n",
       "心率           84.3 (13.1)   84.8 (13.0)   86.1 (13.1)   85.4 (12.7)   \n",
       "同型半胱氨酸        10.9 (5.1)     9.7 (3.9)    10.0 (3.5)     8.0 (3.7)   \n",
       "收缩压         127.2 (18.8)  125.8 (18.3)  127.7 (19.2)  119.4 (14.8)   \n",
       "舒张压          74.4 (11.0)   73.5 (10.7)   74.6 (10.8)   71.1 (10.1)   \n",
       "甘油三酯           1.4 (1.1)     1.4 (1.4)     1.4 (0.7)     1.1 (0.8)   \n",
       "总胆固醇           4.7 (0.9)     4.9 (0.9)     4.9 (1.0)     4.5 (0.8)   \n",
       "高密度脂蛋白         1.3 (0.3)     1.4 (0.4)     1.4 (0.4)     1.4 (0.3)   \n",
       "低密度脂蛋白         2.7 (0.7)     2.7 (0.8)     2.8 (0.8)     2.4 (0.7)   \n",
       "空腹血糖           5.2 (1.1)     5.1 (1.1)     5.1 (1.3)     4.9 (0.7)   \n",
       "糖化血红蛋白A1       7.2 (0.8)     7.0 (0.9)     7.0 (0.8)     6.8 (0.6)   \n",
       "糖化血红蛋白A1c      5.9 (0.7)     5.8 (0.8)     5.8 (0.7)     5.6 (0.5)   \n",
       "中性粒细胞(%)      55.1 (8.2)    55.0 (8.2)    55.0 (8.3)    55.2 (8.8)   \n",
       "淋巴细胞(%)       34.8 (7.6)    35.0 (7.6)    35.4 (8.0)    35.2 (8.1)   \n",
       "单核细胞(%)        7.2 (1.7)     7.0 (1.7)     6.7 (1.8)     7.0 (1.6)   \n",
       "嗜碱性粒细胞(%)      0.6 (0.3)     0.6 (0.3)     0.5 (0.3)     0.6 (0.3)   \n",
       "嗜酸性粒细胞(%)      2.3 (1.9)     2.4 (1.9)     2.4 (1.8)     2.1 (1.7)   \n",
       "红细胞计数          4.8 (0.5)     4.7 (0.5)     4.7 (0.5)     4.6 (0.5)   \n",
       "血小板计数       245.8 (59.0)  249.1 (58.5)  250.1 (59.2)  246.2 (58.3)   \n",
       "白细胞计数          6.3 (1.5)     6.3 (1.6)     6.3 (1.6)     5.9 (1.5)   \n",
       "血红蛋白        144.1 (15.7)  143.3 (15.7)  142.2 (15.6)  138.0 (14.8)   \n",
       "红细胞压积         43.2 (4.1)    43.0 (4.2)    43.2 (4.3)    41.7 (3.9)   \n",
       "平均红细胞体积       90.6 (5.1)    90.7 (5.0)    91.3 (5.5)    90.2 (5.2)   \n",
       "平均血红蛋白含量      30.2 (2.1)    30.2 (2.1)    30.0 (2.2)    29.9 (2.2)   \n",
       "平均血红蛋白浓度    333.0 (10.9)  333.2 (10.4)  328.8 (10.1)  331.0 (11.6)   \n",
       "红细胞分布宽度       12.6 (1.1)    12.7 (1.1)    12.8 (1.1)    12.6 (1.1)   \n",
       "平均血小板体积       10.7 (0.9)    10.6 (0.9)    10.3 (1.0)    10.8 (1.0)   \n",
       "血小板压积          0.3 (0.1)     0.3 (0.1)     0.3 (0.1)     0.3 (0.1)   \n",
       "中性粒细胞          3.5 (1.2)     3.5 (1.2)     3.5 (1.2)     3.3 (1.2)   \n",
       "淋巴细胞           2.2 (0.6)     2.2 (0.6)     2.2 (0.7)     2.0 (0.6)   \n",
       "单核细胞           0.5 (0.1)     0.4 (0.1)     0.4 (0.1)     0.4 (0.1)   \n",
       "嗜酸性粒细胞         0.1 (0.1)     0.1 (0.1)     0.1 (0.1)     0.1 (0.1)   \n",
       "嗜碱性粒细胞         0.0 (0.0)     0.0 (0.0)     0.0 (0.0)     0.0 (0.0)   \n",
       "谷丙转氨酶        21.0 (17.4)   20.8 (16.5)   21.8 (20.0)   17.4 (13.6)   \n",
       "谷草转氨酶        20.3 (10.2)    19.6 (8.8)    20.4 (9.7)    18.9 (7.6)   \n",
       "碱性磷酸酶        72.4 (20.6)   72.9 (21.3)   72.2 (20.7)   65.8 (19.0)   \n",
       "腺苷酸脱氨酶         8.5 (1.8)     8.3 (1.8)     8.8 (2.1)     8.1 (1.8)   \n",
       "甘脯二肽氨基肽酶     77.5 (16.1)   80.1 (17.2)   79.2 (18.1)   74.4 (14.4)   \n",
       "α-岩藻糖苷酶       19.9 (4.9)    20.2 (4.8)    21.2 (5.2)    20.6 (4.8)   \n",
       "三碘甲腺原氨酸        1.5 (0.2)     1.5 (0.4)     1.6 (0.2)     1.5 (0.2)   \n",
       "四碘甲状腺原氨酸    100.1 (17.1)  100.9 (17.2)  102.7 (16.5)  100.2 (18.9)   \n",
       "促甲状腺素          2.0 (1.2)     2.0 (1.3)     2.0 (1.5)     1.9 (1.5)   \n",
       "游离甲状腺素        13.9 (1.5)    13.6 (1.5)    14.2 (1.6)    13.4 (1.7)   \n",
       "甲状腺过氧化物酶抗体  27.1 (134.4)  18.2 (100.9)   18.3 (97.9)  43.5 (155.5)   \n",
       "总胆红素          11.7 (5.0)    11.4 (5.0)    11.4 (5.0)    10.9 (5.0)   \n",
       "直接胆红素          4.0 (1.5)     4.0 (1.5)     4.1 (1.5)     3.8 (1.5)   \n",
       "间接胆红素          7.7 (3.7)     7.4 (3.6)     7.4 (3.6)     7.1 (3.7)   \n",
       "总胆汁酸           4.7 (2.8)     4.9 (2.7)     5.1 (3.1)     4.4 (2.9)   \n",
       "肌酐           72.4 (21.0)   71.0 (23.3)   71.8 (25.4)   65.9 (14.4)   \n",
       "\n",
       "                 2022-01       2023-01       2021-02       2022-02  \\\n",
       "item_name                                                            \n",
       "心率           84.7 (11.8)   86.5 (12.0)   86.0 (12.8)   85.5 (12.3)   \n",
       "同型半胱氨酸         8.2 (3.2)     8.9 (2.5)     8.7 (4.2)     9.0 (3.5)   \n",
       "收缩压         119.5 (14.8)  121.7 (14.2)  120.0 (14.8)  119.9 (14.7)   \n",
       "舒张压           71.4 (9.8)    73.8 (9.5)    71.1 (9.8)    71.3 (9.7)   \n",
       "甘油三酯           1.1 (0.8)     1.2 (0.8)     1.1 (0.9)     1.2 (1.1)   \n",
       "总胆固醇           4.7 (0.9)     4.7 (0.9)     4.4 (0.9)     4.7 (0.9)   \n",
       "高密度脂蛋白         1.5 (0.4)     1.4 (0.3)     1.4 (0.4)     1.5 (0.4)   \n",
       "低密度脂蛋白         2.5 (0.7)     2.6 (0.7)     2.4 (0.7)     2.6 (0.7)   \n",
       "空腹血糖           4.8 (0.7)     4.9 (0.7)     4.8 (0.7)     4.9 (0.7)   \n",
       "糖化血红蛋白A1       6.9 (0.7)     7.0 (0.8)     6.7 (0.6)     7.0 (0.9)   \n",
       "糖化血红蛋白A1c      5.7 (0.6)     5.8 (0.7)     5.6 (0.5)     5.7 (0.8)   \n",
       "中性粒细胞(%)      53.5 (8.5)    55.0 (8.5)    55.2 (8.5)    53.8 (8.5)   \n",
       "淋巴细胞(%)       36.8 (8.0)    35.5 (7.9)    35.0 (7.9)    36.5 (8.0)   \n",
       "单核细胞(%)        7.0 (1.6)     6.8 (1.6)     7.1 (1.7)     7.0 (1.6)   \n",
       "嗜碱性粒细胞(%)      0.6 (0.3)     0.5 (0.3)     0.6 (0.3)     0.6 (0.3)   \n",
       "嗜酸性粒细胞(%)      2.2 (1.6)     2.2 (1.6)     2.1 (1.6)     2.2 (1.7)   \n",
       "红细胞计数          4.6 (0.5)     4.6 (0.5)     4.7 (0.5)     4.6 (0.5)   \n",
       "血小板计数       249.6 (57.3)  254.4 (63.6)  247.4 (56.3)  251.3 (57.0)   \n",
       "白细胞计数          6.0 (1.5)     6.1 (1.5)     6.0 (1.5)     6.1 (1.5)   \n",
       "血红蛋白        137.8 (14.3)  135.4 (14.0)  138.9 (15.1)  137.9 (15.2)   \n",
       "红细胞压积         41.6 (3.7)    41.3 (3.8)    41.9 (4.0)    41.6 (4.0)   \n",
       "平均红细胞体积       90.4 (5.2)    90.8 (5.2)    90.0 (5.0)    90.1 (5.0)   \n",
       "平均血红蛋白含量      29.9 (2.2)    29.7 (2.1)    29.8 (2.2)    29.9 (2.1)   \n",
       "平均血红蛋白浓度    330.9 (10.8)  327.4 (10.0)  331.1 (11.5)  331.3 (10.9)   \n",
       "红细胞分布宽度       12.6 (1.1)    12.9 (1.2)    12.7 (1.1)    12.7 (1.1)   \n",
       "平均血小板体积       10.8 (1.0)    10.5 (1.1)    10.8 (1.0)    10.7 (0.9)   \n",
       "血小板压积          0.3 (0.1)     0.3 (0.1)     0.3 (0.1)     0.3 (0.1)   \n",
       "中性粒细胞          3.3 (1.1)     3.4 (1.1)     3.4 (1.2)     3.3 (1.2)   \n",
       "淋巴细胞           2.2 (0.6)     2.1 (0.6)     2.1 (0.6)     2.2 (0.6)   \n",
       "单核细胞           0.4 (0.1)     0.4 (0.1)     0.4 (0.1)     0.4 (0.1)   \n",
       "嗜酸性粒细胞         0.1 (0.1)     0.1 (0.1)     0.1 (0.1)     0.1 (0.1)   \n",
       "嗜碱性粒细胞         0.0 (0.0)     0.0 (0.0)     0.0 (0.0)     0.0 (0.0)   \n",
       "谷丙转氨酶        18.5 (18.3)   20.5 (19.1)   17.7 (17.9)   18.8 (15.7)   \n",
       "谷草转氨酶         20.7 (9.9)    20.7 (9.0)   19.0 (11.7)   20.8 (10.6)   \n",
       "碱性磷酸酶        65.3 (19.3)   66.0 (19.3)   65.1 (18.7)   64.8 (18.4)   \n",
       "腺苷酸脱氨酶         7.8 (1.8)     8.5 (2.1)     8.7 (2.3)     8.4 (2.2)   \n",
       "甘脯二肽氨基肽酶     78.3 (17.6)   72.2 (15.2)   75.5 (16.1)   79.1 (18.1)   \n",
       "α-岩藻糖苷酶       20.5 (4.8)    21.7 (5.1)    20.6 (5.0)    20.4 (4.9)   \n",
       "三碘甲腺原氨酸        1.5 (0.2)     1.6 (0.4)     1.4 (0.3)     1.5 (0.2)   \n",
       "四碘甲状腺原氨酸     98.9 (15.9)  102.5 (17.7)   98.8 (16.7)   97.8 (16.2)   \n",
       "促甲状腺素          1.9 (1.3)     1.8 (1.2)     1.9 (3.6)     1.8 (1.4)   \n",
       "游离甲状腺素        13.4 (1.6)    13.7 (2.2)    13.2 (1.5)    13.2 (1.6)   \n",
       "甲状腺过氧化物酶抗体  46.8 (142.4)  46.9 (145.7)  47.8 (166.6)  53.8 (174.5)   \n",
       "总胆红素          10.7 (4.8)    10.9 (4.7)    11.1 (5.0)    11.0 (5.1)   \n",
       "直接胆红素          3.9 (1.5)     3.9 (1.4)     3.9 (1.5)     4.0 (1.6)   \n",
       "间接胆红素          6.8 (3.4)     7.0 (3.4)     7.2 (3.6)     7.0 (3.7)   \n",
       "总胆汁酸           4.6 (2.8)     5.1 (3.5)    5.2 (15.2)    5.5 (13.4)   \n",
       "肌酐           64.5 (15.3)   63.5 (16.3)   66.8 (19.2)   65.6 (19.3)   \n",
       "\n",
       "                 2023-02  Missing       Overall  \n",
       "item_name                                        \n",
       "心率           85.4 (12.0)     1630   85.5 (12.4)  \n",
       "同型半胱氨酸        10.2 (4.7)    14200     8.9 (4.2)  \n",
       "收缩压         120.9 (15.1)     1631  121.2 (15.6)  \n",
       "舒张压           72.1 (9.9)     1629   72.0 (10.0)  \n",
       "甘油三酯           1.2 (0.9)      218     1.2 (1.0)  \n",
       "总胆固醇           4.7 (0.9)      218     4.6 (0.9)  \n",
       "高密度脂蛋白         1.5 (0.4)      218     1.5 (0.4)  \n",
       "低密度脂蛋白         2.6 (0.7)      218     2.6 (0.7)  \n",
       "空腹血糖           4.8 (0.8)       67     4.9 (0.8)  \n",
       "糖化血红蛋白A1       7.0 (0.8)    12224     6.9 (0.7)  \n",
       "糖化血红蛋白A1c      5.8 (0.7)    12224     5.7 (0.6)  \n",
       "中性粒细胞(%)      54.0 (8.0)       63    54.5 (8.4)  \n",
       "淋巴细胞(%)       36.4 (7.6)       63    35.8 (7.9)  \n",
       "单核细胞(%)        6.7 (1.6)       63     6.9 (1.6)  \n",
       "嗜碱性粒细胞(%)      0.6 (0.3)       63     0.6 (0.3)  \n",
       "嗜酸性粒细胞(%)      2.3 (1.8)       63     2.2 (1.7)  \n",
       "红细胞计数          4.6 (0.5)       63     4.6 (0.5)  \n",
       "血小板计数       255.3 (57.3)       65  250.6 (58.0)  \n",
       "白细胞计数          6.2 (1.6)       63     6.1 (1.5)  \n",
       "血红蛋白        137.2 (14.7)       63  138.6 (15.1)  \n",
       "红细胞压积         41.8 (4.0)       63    41.9 (4.0)  \n",
       "平均红细胞体积       90.6 (5.1)       63    90.4 (5.1)  \n",
       "平均血红蛋白含量      29.7 (2.1)       63    29.9 (2.1)  \n",
       "平均血红蛋白浓度     327.6 (9.8)       63  330.2 (10.9)  \n",
       "红细胞分布宽度       13.0 (1.1)       64    12.7 (1.1)  \n",
       "平均血小板体积       10.6 (1.0)      218    10.7 (1.0)  \n",
       "血小板压积          0.3 (0.1)      218     0.3 (0.1)  \n",
       "中性粒细胞          3.4 (1.1)       63     3.4 (1.2)  \n",
       "淋巴细胞           2.2 (0.6)       63     2.2 (0.6)  \n",
       "单核细胞           0.4 (0.1)       63     0.4 (0.1)  \n",
       "嗜酸性粒细胞         0.1 (0.1)       63     0.1 (0.1)  \n",
       "嗜碱性粒细胞         0.0 (0.0)       63     0.0 (0.0)  \n",
       "谷丙转氨酶        19.5 (17.2)       54   19.1 (17.2)  \n",
       "谷草转氨酶         20.8 (7.8)    14606    20.0 (9.9)  \n",
       "碱性磷酸酶        64.2 (18.2)       86   66.2 (19.2)  \n",
       "腺苷酸脱氨酶         8.8 (2.5)    15688     8.5 (2.1)  \n",
       "甘脯二肽氨基肽酶     75.7 (17.4)    14905   77.0 (16.9)  \n",
       "α-岩藻糖苷酶       21.8 (5.3)    15688    20.8 (5.1)  \n",
       "三碘甲腺原氨酸        1.6 (0.3)    13513     1.5 (0.3)  \n",
       "四碘甲状腺原氨酸     97.2 (17.3)     9680   99.3 (17.1)  \n",
       "促甲状腺素          2.2 (8.4)     9680     2.0 (3.7)  \n",
       "游离甲状腺素        13.5 (1.8)    13774    13.5 (1.7)  \n",
       "甲状腺过氧化物酶抗体  65.8 (205.9)    16210  41.3 (155.1)  \n",
       "总胆红素          10.9 (4.8)       54    11.0 (4.9)  \n",
       "直接胆红素          3.9 (1.5)       54     3.9 (1.5)  \n",
       "间接胆红素          7.0 (3.4)       70     7.1 (3.6)  \n",
       "总胆汁酸           5.6 (6.4)    14908     5.1 (8.9)  \n",
       "肌酐           64.5 (17.4)       67   66.3 (18.8)  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def show_cont_table(my_table_value):\n",
    "    my_table_value = mytable.cont_table\n",
    "    my_table_value.loc[l_columns].columns\n",
    "    my_table_value = my_table_value.loc[l_columns, col_order]\n",
    "    my_table_value.index = df_meta_groups.loc[l_columns][\"item_name\"]\n",
    "    return my_table_value\n",
    "\n",
    "mytable = tableone.TableOne(df_table1plus_3p_revMM[df_table1plus_3p_revMM[\"month\"].isin([12,1,2])], \n",
    "                                l_columns, [], \"year-month\")\n",
    "show_cont_table(mytable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15c27df0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "l_heart = list(filter(lambda x: x[0:5]==\"HEART\", l_high_lighted))\n",
    "def get_heart_status(x):\n",
    "    for tag in l_heart:\n",
    "        if x[tag] > 0:\n",
    "            return tag[6:]\n",
    "\n",
    "df_table1plus_3p_revMM[\"HEART.Status\"] = df_table1plus_3p_revMM.apply(lambda x: get_heart_status(x), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dd14f151",
   "metadata": {
    "tags": []
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Grouped by period</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Control-2021</th>\n",
       "      <th>Control-2022</th>\n",
       "      <th>Test-2023</th>\n",
       "      <th>P-Value (adjusted)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <th></th>\n",
       "      <td>88920</td>\n",
       "      <td>90751</td>\n",
       "      <td>56010</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">gender, n (%)</th>\n",
       "      <th>female</th>\n",
       "      <td>43947 (49.4)</td>\n",
       "      <td>44358 (48.9)</td>\n",
       "      <td>27765 (49.6)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>44973 (50.6)</td>\n",
       "      <td>46393 (51.1)</td>\n",
       "      <td>28245 (50.4)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>42.6 (14.2)</td>\n",
       "      <td>42.9 (14.0)</td>\n",
       "      <td>43.5 (14.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>height, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>165.7 (8.3)</td>\n",
       "      <td>166.0 (8.3)</td>\n",
       "      <td>165.9 (8.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUNG.Nodule, n (%)</th>\n",
       "      <th>1.0</th>\n",
       "      <td>20018 (22.5)</td>\n",
       "      <td>22807 (25.1)</td>\n",
       "      <td>15507 (27.7)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">LUNG.Normal, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>78126 (87.9)</td>\n",
       "      <td>80969 (89.2)</td>\n",
       "      <td>50239 (89.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>10794 (12.1)</td>\n",
       "      <td>9782 (10.8)</td>\n",
       "      <td>5771 (10.3)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">LIVER.Steatosis, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>59438 (66.8)</td>\n",
       "      <td>58527 (64.5)</td>\n",
       "      <td>35491 (63.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>29482 (33.2)</td>\n",
       "      <td>32224 (35.5)</td>\n",
       "      <td>20519 (36.6)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99 rows × 4 columns</p>\n",
       "</div><br />"
      ],
      "text/plain": [
       "                                          Grouped by period                                               \n",
       "                                               Control-2021  Control-2022     Test-2023 P-Value (adjusted)\n",
       "n                                                     88920         90751         56010                   \n",
       "gender, n (%)                      female      43947 (49.4)  44358 (48.9)  27765 (49.6)              1.000\n",
       "                                   male        44973 (50.6)  46393 (51.1)  28245 (50.4)                   \n",
       "age, mean (SD)                                  42.6 (14.2)   42.9 (14.0)   43.5 (14.1)             <0.001\n",
       "height, mean (SD)                               165.7 (8.3)   166.0 (8.3)   165.9 (8.3)             <0.001\n",
       "weight, mean (SD)                               64.4 (12.5)   64.7 (12.7)   65.0 (12.8)             <0.001\n",
       " waist-circumference, mean (SD)                 83.3 (10.1)   82.3 (10.1)   82.4 (10.6)             <0.001\n",
       "HR, mean (SD)                                   81.3 (12.7)   81.5 (12.6)   82.2 (12.6)             <0.001\n",
       "HCY, mean (SD)                                    9.9 (5.2)    10.5 (4.9)    10.5 (4.8)             <0.001\n",
       "SBP, mean (SD)                                 120.7 (17.1)  121.0 (17.3)  122.7 (17.1)             <0.001\n",
       "DBP, mean (SD)                                  71.8 (11.1)   72.0 (11.1)   73.2 (11.0)             <0.001\n",
       "TG, mean (SD)                                     1.4 (1.1)     1.4 (1.2)     1.4 (1.2)              0.045\n",
       "TC, mean (SD)                                     4.7 (0.9)     4.7 (0.9)     4.8 (0.9)             <0.001\n",
       "HDL-C, mean (SD)                                  1.3 (0.4)     1.4 (0.4)     1.3 (0.4)             <0.001\n",
       "LDL-C, mean (SD)                                  2.6 (0.7)     2.7 (0.7)     2.7 (0.7)             <0.001\n",
       "FPG, mean (SD)                                    4.9 (1.0)     4.9 (1.0)     4.9 (1.0)             <0.001\n",
       "HbA1, mean (SD)                                   6.9 (0.8)     6.9 (0.8)     7.0 (0.8)             <0.001\n",
       "HbA1c, mean (SD)                                  5.7 (0.7)     5.7 (0.7)     5.8 (0.7)             <0.001\n",
       "NEUT%, mean (SD)                                 55.9 (8.2)    55.8 (8.1)    55.5 (8.2)             <0.001\n",
       "LYMPH%, mean (SD)                                34.2 (7.6)    34.6 (7.6)    34.8 (7.7)             <0.001\n",
       "MONO%, mean (SD)                                  7.0 (1.7)     6.7 (1.6)     6.8 (1.7)             <0.001\n",
       "BASO%, mean (SD)                                  0.6 (0.3)     0.6 (0.3)     0.6 (0.3)             <0.001\n",
       "EOS%, mean (SD)                                   2.3 (1.8)     2.3 (1.8)     2.4 (1.9)             <0.001\n",
       "RBC, mean (SD)                                    4.8 (0.5)     4.8 (0.5)     4.8 (0.5)             <0.001\n",
       "PLT, mean (SD)                                 240.4 (57.5)  242.5 (57.8)  245.9 (58.3)             <0.001\n",
       "WBC, mean (SD)                                    6.1 (1.6)     6.1 (1.6)     6.2 (1.8)             <0.001\n",
       "Hb, mean (SD)                                  143.7 (16.3)  143.5 (16.2)  142.7 (15.9)             <0.001\n",
       "Hct, mean (SD)                                   43.2 (4.3)    43.0 (4.3)    43.2 (4.3)             <0.001\n",
       "MCV, mean (SD)                                   90.6 (5.1)    90.4 (5.1)    90.8 (5.2)             <0.001\n",
       "MCH, mean (SD)                                   30.1 (2.1)    30.1 (2.1)    30.0 (2.1)             <0.001\n",
       "MCHC, mean (SD)                                332.1 (10.7)  333.3 (10.6)  329.6 (10.4)             <0.001\n",
       "RDW, mean (SD)                                   12.7 (1.1)    12.8 (1.1)    12.8 (1.1)             <0.001\n",
       "MPV, mean (SD)                                   10.7 (1.0)    10.6 (1.0)    10.5 (1.0)             <0.001\n",
       "PCT, mean (SD)                                    0.3 (0.1)     0.3 (0.1)     0.3 (0.1)              0.010\n",
       "NEUT, mean (SD)                                   3.5 (1.2)     3.4 (1.2)     3.5 (1.2)              0.415\n",
       "LYMPH, mean (SD)                                  2.1 (0.6)     2.1 (0.6)     2.1 (1.0)             <0.001\n",
       "MONO, mean (SD)                                   0.4 (0.1)     0.4 (0.1)     0.4 (0.1)             <0.001\n",
       "EOS, mean (SD)                                    0.1 (0.1)     0.1 (0.1)     0.1 (0.1)             <0.001\n",
       "BASO, mean (SD)                                   0.0 (0.0)     0.0 (0.0)     0.0 (0.0)             <0.001\n",
       "ALT, mean (SD)                                  21.7 (21.4)   22.0 (20.4)   22.2 (20.9)              0.016\n",
       "AST, mean (SD)                                  20.2 (12.6)   20.4 (12.6)   20.3 (12.8)              1.000\n",
       "ALP, mean (SD)                                  70.9 (21.6)   70.6 (21.2)   69.6 (20.6)             <0.001\n",
       "ADA, mean (SD)                                    8.6 (2.3)     8.5 (2.3)     8.8 (2.4)             <0.001\n",
       "GPDA, mean (SD)                                 80.5 (18.7)   80.7 (18.8)   79.0 (18.6)             <0.001\n",
       "AFU, mean (SD)                                   20.4 (5.2)    20.4 (5.3)    21.7 (5.5)             <0.001\n",
       "T3, mean (SD)                                     1.5 (0.3)     1.5 (0.3)     1.5 (0.3)             <0.001\n",
       "T4, mean (SD)                                   96.9 (16.5)   96.1 (16.3)   97.4 (16.5)             <0.001\n",
       "TSH, mean (SD)                                    1.9 (1.9)     1.8 (1.8)     1.8 (2.5)              0.097\n",
       "FT4, mean (SD)                                   13.2 (1.6)    13.3 (1.6)    13.5 (1.7)             <0.001\n",
       "TPOAb, mean (SD)                               30.2 (135.2)  30.9 (137.4)  33.3 (142.0)              1.000\n",
       "TBIL, mean (SD)                                  12.2 (5.5)    12.2 (5.6)    11.8 (5.4)             <0.001\n",
       "DBIL, mean (SD)                                   4.3 (1.7)     4.3 (1.7)     4.2 (1.9)             <0.001\n",
       "IBIL, mean (SD)                                   7.9 (4.0)     7.9 (4.1)     7.6 (3.8)             <0.001\n",
       "TBA, mean (SD)                                    4.5 (4.8)     4.6 (4.5)     4.9 (4.2)             <0.001\n",
       "Cr, mean (SD)                                   72.8 (18.1)   72.2 (18.4)   72.4 (19.0)             <0.001\n",
       "HEART.Normal, n (%)                0.0         50532 (56.8)  50900 (56.1)  32495 (58.0)             <0.001\n",
       "                                   1.0         38388 (43.2)  39851 (43.9)  23515 (42.0)                   \n",
       "HEART.SinusRhythm, n (%)           0.0         71184 (80.1)  71184 (78.4)  43986 (78.5)             <0.001\n",
       "                                   1.0         17736 (19.9)  19567 (21.6)  12024 (21.5)                   \n",
       "HEART.SinusBradycardia, n (%)      0.0         83712 (94.1)  84381 (93.0)  53161 (94.9)             <0.001\n",
       "                                   1.0           5208 (5.9)    6370 (7.0)    2849 (5.1)                   \n",
       "HEART.SinusArrhythmia, n (%)       0.0         85131 (95.7)  86591 (95.4)  53175 (94.9)             <0.001\n",
       "                                   1.0           3789 (4.3)    4160 (4.6)    2835 (5.1)                   \n",
       "HEART.AtrialFibrillation, n (%)    0.0         87917 (98.9)  89625 (98.8)  55350 (98.8)              1.000\n",
       "                                   1.0           1003 (1.1)    1126 (1.2)     660 (1.2)                   \n",
       "HEART.SinusTachycardia, n (%)      0.0         87773 (98.7)  89692 (98.8)  55158 (98.5)             <0.001\n",
       "                                   1.0           1147 (1.3)    1059 (1.2)     852 (1.5)                   \n",
       "HEART.T_change, n (%)              0.0         80964 (91.1)  82107 (90.5)  50670 (90.5)              0.001\n",
       "                                   1.0           7956 (8.9)    8644 (9.5)    5340 (9.5)                   \n",
       "HEART.ST_change, n (%)             0.0         82234 (92.5)  82656 (91.1)  50883 (90.8)             <0.001\n",
       "                                   1.0           6686 (7.5)    8095 (8.9)    5127 (9.2)                   \n",
       "HEART.ElectricAxisDeviation, n (%) 0.0         84092 (94.6)  85790 (94.5)  52895 (94.4)              1.000\n",
       "                                   1.0           4828 (5.4)    4961 (5.5)    3115 (5.6)                   \n",
       "HEART.LVH, n (%)                   0.0         86290 (97.0)  88044 (97.0)  54370 (97.1)              1.000\n",
       "                                   1.0           2630 (3.0)    2707 (3.0)    1640 (2.9)                   \n",
       "HEART.HeartBlocks, n (%)           0.0         86238 (97.0)  87902 (96.9)  54349 (97.0)              1.000\n",
       "                                   1.0           2682 (3.0)    2849 (3.1)    1661 (3.0)                   \n",
       "HEART.ExtraSystole, n (%)          0.0         87728 (98.7)  89387 (98.5)  55217 (98.6)              1.000\n",
       "                                   1.0           1192 (1.3)    1364 (1.5)     793 (1.4)                   \n",
       "LUNG.GroundGlassOpacity, n (%)     0.0         79945 (89.9)  78835 (86.9)  47823 (85.4)             <0.001\n",
       "                                   1.0          8975 (10.1)  11916 (13.1)   8187 (14.6)                   \n",
       "LUNG.Effusion, n (%)               0.0         88459 (99.5)  90028 (99.2)  55606 (99.3)             <0.001\n",
       "                                   1.0            461 (0.5)     723 (0.8)     404 (0.7)                   \n",
       "LUNG.Fibrosis, n (%)               0.0         74179 (83.4)  75108 (82.8)  46596 (83.2)              0.061\n",
       "                                   1.0         14741 (16.6)  15643 (17.2)   9414 (16.8)                   \n",
       "LUNG.Calcification, n (%)          0.0         73774 (83.0)  70077 (77.2)  41409 (73.9)             <0.001\n",
       "                                   1.0         15146 (17.0)  20674 (22.8)  14601 (26.1)                   \n",
       "LUNG.ProliferativeLesion, n (%)    0.0         66158 (74.4)  63466 (69.9)  38721 (69.1)             <0.001\n",
       "                                   1.0         22762 (25.6)  27285 (30.1)  17289 (30.9)                   \n",
       "LUNG.SolidNodule, n (%)            0.0         88038 (99.0)  89509 (98.6)  55136 (98.4)             <0.001\n",
       "                                   1.0            882 (1.0)    1242 (1.4)     874 (1.6)                   \n",
       "LUNG.SmallNodule, n (%)            0.0         79214 (89.1)  80790 (89.0)  49012 (87.5)             <0.001\n",
       "                                   1.0          9706 (10.9)   9961 (11.0)   6998 (12.5)                   \n",
       "LUNG.Nodule, n (%)                 0.0         68902 (77.5)  67944 (74.9)  40503 (72.3)             <0.001\n",
       "                                   1.0         20018 (22.5)  22807 (25.1)  15507 (27.7)                   \n",
       "LUNG.Normal, n (%)                 0.0         78126 (87.9)  80969 (89.2)  50239 (89.7)             <0.001\n",
       "                                   1.0         10794 (12.1)   9782 (10.8)   5771 (10.3)                   \n",
       "LIVER.Steatosis, n (%)             0.0         59438 (66.8)  58527 (64.5)  35491 (63.4)             <0.001\n",
       "                                   1.0         29482 (33.2)  32224 (35.5)  20519 (36.6)                   "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_table1plus1 = df_table1plus.copy()\n",
    "\n",
    "l_basics = [\"gender\", \"age\", \"v000760\", \"v000761\", \"v002266\"]\n",
    "l_basics_en = [\"gender\", \"age\", \"height\", \"weight\", \" waist-circumference\"]\n",
    "df_table1plus1[\"HEART.Status\"] = df_table1plus1.apply(lambda x: get_heart_status(x), axis=1)\n",
    "df_sub = df_table1plus1[\n",
    "     l_basics+[\"period\"] + l_columns+l_category\n",
    "]\n",
    "\n",
    "l_cat_en = l_category[0:1] + list(df_meta_groups.loc[l_category[1:]][\"item_name_en\"])\n",
    "l_col_en = list(df_meta_groups.loc[l_columns][\"item_name_en\"])\n",
    "df_sub.columns = l_basics_en + [ \"period\"] + l_col_en + l_cat_en\n",
    "\n",
    "mytable = tableone.TableOne(df_sub, \n",
    "                            l_basics_en + l_col_en+l_cat_en,\n",
    "                            [\"gender\"]+l_cat_en, \n",
    "                            groupby=\"period\", \n",
    "                            pval=True, \n",
    "                            overall=False, missing=False, pval_adjust=\"bonferroni\")\n",
    "mytable.to_excel(f'{workdir}/TableS1.xlsx')\n",
    "mytable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6b4b633f",
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Grouped by period</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Control-2021</th>\n",
       "      <th>Control-2022</th>\n",
       "      <th>Test-2023</th>\n",
       "      <th>P-Value (adjusted)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <th></th>\n",
       "      <td>23838</td>\n",
       "      <td>23838</td>\n",
       "      <td>23838</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">gender, n (%)</th>\n",
       "      <th>female</th>\n",
       "      <td>12734 (53.4)</td>\n",
       "      <td>12734 (53.4)</td>\n",
       "      <td>12734 (53.4)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>11104 (46.6)</td>\n",
       "      <td>11104 (46.6)</td>\n",
       "      <td>11104 (46.6)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>43.3 (14.4)</td>\n",
       "      <td>44.3 (14.4)</td>\n",
       "      <td>45.3 (14.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>height, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>165.3 (8.3)</td>\n",
       "      <td>165.5 (8.2)</td>\n",
       "      <td>165.5 (8.2)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>63.6 (12.2)</td>\n",
       "      <td>64.1 (12.3)</td>\n",
       "      <td>64.0 (12.4)</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>waist-circumference, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>83.7 (9.7)</td>\n",
       "      <td>83.8 (9.6)</td>\n",
       "      <td>83.2 (10.0)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HR, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>82.5 (12.8)</td>\n",
       "      <td>82.5 (12.5)</td>\n",
       "      <td>82.5 (12.4)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HCY, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>9.5 (4.9)</td>\n",
       "      <td>10.2 (4.4)</td>\n",
       "      <td>10.7 (4.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SBP, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>121.2 (16.9)</td>\n",
       "      <td>122.4 (17.1)</td>\n",
       "      <td>123.3 (17.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBP, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>71.9 (10.8)</td>\n",
       "      <td>72.6 (10.9)</td>\n",
       "      <td>73.4 (10.9)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TG, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.4 (1.1)</td>\n",
       "      <td>1.4 (1.1)</td>\n",
       "      <td>1.4 (1.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.6 (0.9)</td>\n",
       "      <td>4.8 (0.9)</td>\n",
       "      <td>4.8 (0.9)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HDL-C, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.3 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LDL-C, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2.7 (0.7)</td>\n",
       "      <td>2.7 (0.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FPG, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.9 (0.9)</td>\n",
       "      <td>4.9 (1.0)</td>\n",
       "      <td>4.9 (1.0)</td>\n",
       "      <td>0.019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>6.9 (0.7)</td>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>7.1 (0.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1c, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>5.7 (0.6)</td>\n",
       "      <td>5.7 (0.7)</td>\n",
       "      <td>5.8 (0.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>55.6 (8.2)</td>\n",
       "      <td>55.1 (8.3)</td>\n",
       "      <td>55.0 (8.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>34.5 (7.6)</td>\n",
       "      <td>35.2 (7.8)</td>\n",
       "      <td>35.3 (7.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>6.8 (1.6)</td>\n",
       "      <td>6.7 (1.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>2.3 (1.8)</td>\n",
       "      <td>2.3 (1.8)</td>\n",
       "      <td>2.4 (1.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.8 (0.5)</td>\n",
       "      <td>4.8 (0.5)</td>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>240.5 (57.5)</td>\n",
       "      <td>243.8 (57.9)</td>\n",
       "      <td>246.3 (58.9)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WBC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>6.0 (1.5)</td>\n",
       "      <td>6.1 (1.6)</td>\n",
       "      <td>6.1 (1.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hb, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>143.0 (16.1)</td>\n",
       "      <td>142.8 (16.1)</td>\n",
       "      <td>141.5 (15.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hct, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>43.1 (4.3)</td>\n",
       "      <td>42.9 (4.2)</td>\n",
       "      <td>43.0 (4.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCV, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>90.7 (5.2)</td>\n",
       "      <td>90.5 (5.1)</td>\n",
       "      <td>90.9 (5.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCH, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>30.1 (2.2)</td>\n",
       "      <td>30.1 (2.2)</td>\n",
       "      <td>29.9 (2.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCHC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>331.1 (10.9)</td>\n",
       "      <td>332.3 (10.6)</td>\n",
       "      <td>328.9 (10.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RDW, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>12.7 (1.1)</td>\n",
       "      <td>12.9 (1.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPV, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>10.7 (1.0)</td>\n",
       "      <td>10.6 (1.0)</td>\n",
       "      <td>10.5 (1.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>3.4 (1.1)</td>\n",
       "      <td>3.4 (1.1)</td>\n",
       "      <td>3.4 (1.1)</td>\n",
       "      <td>0.959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>2.0 (0.6)</td>\n",
       "      <td>2.1 (0.7)</td>\n",
       "      <td>2.1 (0.9)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>20.4 (18.5)</td>\n",
       "      <td>21.0 (17.7)</td>\n",
       "      <td>21.5 (22.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AST, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>19.9 (14.4)</td>\n",
       "      <td>20.2 (8.9)</td>\n",
       "      <td>20.3 (15.9)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALP, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>70.1 (20.6)</td>\n",
       "      <td>70.5 (20.9)</td>\n",
       "      <td>69.0 (20.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADA, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>8.5 (2.2)</td>\n",
       "      <td>8.3 (2.1)</td>\n",
       "      <td>8.8 (2.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GPDA, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>78.5 (17.2)</td>\n",
       "      <td>79.8 (18.1)</td>\n",
       "      <td>78.4 (18.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFU, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>20.7 (5.2)</td>\n",
       "      <td>20.5 (5.1)</td>\n",
       "      <td>21.6 (5.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T3, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>97.2 (16.5)</td>\n",
       "      <td>95.8 (16.2)</td>\n",
       "      <td>97.4 (16.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSH, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.9 (2.0)</td>\n",
       "      <td>1.9 (1.5)</td>\n",
       "      <td>1.9 (3.2)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT4, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>13.3 (1.5)</td>\n",
       "      <td>13.1 (1.5)</td>\n",
       "      <td>13.4 (1.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TPOAb, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>32.4 (138.9)</td>\n",
       "      <td>32.0 (137.6)</td>\n",
       "      <td>34.7 (143.9)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBIL, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>12.0 (5.3)</td>\n",
       "      <td>11.9 (5.3)</td>\n",
       "      <td>11.7 (5.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBIL, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.2 (1.6)</td>\n",
       "      <td>4.2 (1.6)</td>\n",
       "      <td>4.2 (1.6)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBIL, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>7.7 (3.9)</td>\n",
       "      <td>7.7 (3.9)</td>\n",
       "      <td>7.5 (3.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBA, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.4 (6.0)</td>\n",
       "      <td>4.6 (5.0)</td>\n",
       "      <td>5.0 (4.6)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cr, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>72.1 (20.5)</td>\n",
       "      <td>71.6 (19.5)</td>\n",
       "      <td>72.0 (21.7)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">HEART.Normal, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>11066 (46.4)</td>\n",
       "      <td>11511 (48.3)</td>\n",
       "      <td>12063 (50.6)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>12772 (53.6)</td>\n",
       "      <td>12327 (51.7)</td>\n",
       "      <td>11775 (49.4)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">HEART.SinusRhythm, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>18020 (75.6)</td>\n",
       "      <td>17762 (74.5)</td>\n",
       "      <td>17622 (73.9)</td>\n",
       "      <td>0.009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>5818 (24.4)</td>\n",
       "      <td>6076 (25.5)</td>\n",
       "      <td>6216 (26.1)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEART.SinusBradycardia, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>22386 (93.9)</td>\n",
       "      <td>22159 (93.0)</td>\n",
       "      <td>22381 (93.9)</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Grouped by period                \\\n",
       "                                            Control-2021  Control-2022   \n",
       "n                                                  23838         23838   \n",
       "gender, n (%)                   female      12734 (53.4)  12734 (53.4)   \n",
       "                                male        11104 (46.6)  11104 (46.6)   \n",
       "age, mean (SD)                               43.3 (14.4)   44.3 (14.4)   \n",
       "height, mean (SD)                            165.3 (8.3)   165.5 (8.2)   \n",
       "weight, mean (SD)                            63.6 (12.2)   64.1 (12.3)   \n",
       " waist-circumference, mean (SD)               83.7 (9.7)    83.8 (9.6)   \n",
       "HR, mean (SD)                                82.5 (12.8)   82.5 (12.5)   \n",
       "HCY, mean (SD)                                 9.5 (4.9)    10.2 (4.4)   \n",
       "SBP, mean (SD)                              121.2 (16.9)  122.4 (17.1)   \n",
       "DBP, mean (SD)                               71.9 (10.8)   72.6 (10.9)   \n",
       "TG, mean (SD)                                  1.4 (1.1)     1.4 (1.1)   \n",
       "TC, mean (SD)                                  4.6 (0.9)     4.8 (0.9)   \n",
       "HDL-C, mean (SD)                               1.3 (0.4)     1.4 (0.4)   \n",
       "LDL-C, mean (SD)                               2.6 (0.7)     2.7 (0.7)   \n",
       "FPG, mean (SD)                                 4.9 (0.9)     4.9 (1.0)   \n",
       "HbA1, mean (SD)                                6.9 (0.7)     7.0 (0.8)   \n",
       "HbA1c, mean (SD)                               5.7 (0.6)     5.7 (0.7)   \n",
       "NEUT%, mean (SD)                              55.6 (8.2)    55.1 (8.3)   \n",
       "LYMPH%, mean (SD)                             34.5 (7.6)    35.2 (7.8)   \n",
       "MONO%, mean (SD)                               7.0 (1.6)     6.8 (1.6)   \n",
       "BASO%, mean (SD)                               0.6 (0.3)     0.6 (0.3)   \n",
       "EOS%, mean (SD)                                2.3 (1.8)     2.3 (1.8)   \n",
       "RBC, mean (SD)                                 4.8 (0.5)     4.8 (0.5)   \n",
       "PLT, mean (SD)                              240.5 (57.5)  243.8 (57.9)   \n",
       "WBC, mean (SD)                                 6.0 (1.5)     6.1 (1.6)   \n",
       "Hb, mean (SD)                               143.0 (16.1)  142.8 (16.1)   \n",
       "Hct, mean (SD)                                43.1 (4.3)    42.9 (4.2)   \n",
       "MCV, mean (SD)                                90.7 (5.2)    90.5 (5.1)   \n",
       "MCH, mean (SD)                                30.1 (2.2)    30.1 (2.2)   \n",
       "MCHC, mean (SD)                             331.1 (10.9)  332.3 (10.6)   \n",
       "RDW, mean (SD)                                12.7 (1.1)    12.7 (1.1)   \n",
       "MPV, mean (SD)                                10.7 (1.0)    10.6 (1.0)   \n",
       "PCT, mean (SD)                                 0.3 (0.1)     0.3 (0.1)   \n",
       "NEUT, mean (SD)                                3.4 (1.1)     3.4 (1.1)   \n",
       "LYMPH, mean (SD)                               2.0 (0.6)     2.1 (0.7)   \n",
       "MONO, mean (SD)                                0.4 (0.1)     0.4 (0.1)   \n",
       "EOS, mean (SD)                                 0.1 (0.1)     0.1 (0.1)   \n",
       "BASO, mean (SD)                                0.0 (0.0)     0.0 (0.0)   \n",
       "ALT, mean (SD)                               20.4 (18.5)   21.0 (17.7)   \n",
       "AST, mean (SD)                               19.9 (14.4)    20.2 (8.9)   \n",
       "ALP, mean (SD)                               70.1 (20.6)   70.5 (20.9)   \n",
       "ADA, mean (SD)                                 8.5 (2.2)     8.3 (2.1)   \n",
       "GPDA, mean (SD)                              78.5 (17.2)   79.8 (18.1)   \n",
       "AFU, mean (SD)                                20.7 (5.2)    20.5 (5.1)   \n",
       "T3, mean (SD)                                  1.5 (0.3)     1.5 (0.3)   \n",
       "T4, mean (SD)                                97.2 (16.5)   95.8 (16.2)   \n",
       "TSH, mean (SD)                                 1.9 (2.0)     1.9 (1.5)   \n",
       "FT4, mean (SD)                                13.3 (1.5)    13.1 (1.5)   \n",
       "TPOAb, mean (SD)                            32.4 (138.9)  32.0 (137.6)   \n",
       "TBIL, mean (SD)                               12.0 (5.3)    11.9 (5.3)   \n",
       "DBIL, mean (SD)                                4.2 (1.6)     4.2 (1.6)   \n",
       "IBIL, mean (SD)                                7.7 (3.9)     7.7 (3.9)   \n",
       "TBA, mean (SD)                                 4.4 (6.0)     4.6 (5.0)   \n",
       "Cr, mean (SD)                                72.1 (20.5)   71.6 (19.5)   \n",
       "HEART.Normal, n (%)             0.0         11066 (46.4)  11511 (48.3)   \n",
       "                                1.0         12772 (53.6)  12327 (51.7)   \n",
       "HEART.SinusRhythm, n (%)        0.0         18020 (75.6)  17762 (74.5)   \n",
       "                                1.0          5818 (24.4)   6076 (25.5)   \n",
       "HEART.SinusBradycardia, n (%)   0.0         22386 (93.9)  22159 (93.0)   \n",
       "\n",
       "                                                                         \n",
       "                                           Test-2023 P-Value (adjusted)  \n",
       "n                                              23838                     \n",
       "gender, n (%)                   female  12734 (53.4)              1.000  \n",
       "                                male    11104 (46.6)                     \n",
       "age, mean (SD)                           45.3 (14.4)             <0.001  \n",
       "height, mean (SD)                        165.5 (8.2)              1.000  \n",
       "weight, mean (SD)                        64.0 (12.4)              0.003  \n",
       " waist-circumference, mean (SD)          83.2 (10.0)              1.000  \n",
       "HR, mean (SD)                            82.5 (12.4)              1.000  \n",
       "HCY, mean (SD)                            10.7 (4.7)             <0.001  \n",
       "SBP, mean (SD)                          123.3 (17.2)             <0.001  \n",
       "DBP, mean (SD)                           73.4 (10.9)             <0.001  \n",
       "TG, mean (SD)                              1.4 (1.1)             <0.001  \n",
       "TC, mean (SD)                              4.8 (0.9)             <0.001  \n",
       "HDL-C, mean (SD)                           1.4 (0.4)             <0.001  \n",
       "LDL-C, mean (SD)                           2.7 (0.7)             <0.001  \n",
       "FPG, mean (SD)                             4.9 (1.0)              0.019  \n",
       "HbA1, mean (SD)                            7.1 (0.8)             <0.001  \n",
       "HbA1c, mean (SD)                           5.8 (0.7)             <0.001  \n",
       "NEUT%, mean (SD)                          55.0 (8.2)             <0.001  \n",
       "LYMPH%, mean (SD)                         35.3 (7.7)             <0.001  \n",
       "MONO%, mean (SD)                           6.7 (1.7)             <0.001  \n",
       "BASO%, mean (SD)                           0.6 (0.3)             <0.001  \n",
       "EOS%, mean (SD)                            2.4 (1.8)             <0.001  \n",
       "RBC, mean (SD)                             4.7 (0.5)             <0.001  \n",
       "PLT, mean (SD)                          246.3 (58.9)             <0.001  \n",
       "WBC, mean (SD)                             6.1 (1.7)             <0.001  \n",
       "Hb, mean (SD)                           141.5 (15.8)             <0.001  \n",
       "Hct, mean (SD)                            43.0 (4.2)             <0.001  \n",
       "MCV, mean (SD)                            90.9 (5.2)             <0.001  \n",
       "MCH, mean (SD)                            29.9 (2.1)             <0.001  \n",
       "MCHC, mean (SD)                         328.9 (10.4)             <0.001  \n",
       "RDW, mean (SD)                            12.9 (1.1)             <0.001  \n",
       "MPV, mean (SD)                            10.5 (1.0)             <0.001  \n",
       "PCT, mean (SD)                             0.3 (0.1)              1.000  \n",
       "NEUT, mean (SD)                            3.4 (1.1)              0.959  \n",
       "LYMPH, mean (SD)                           2.1 (0.9)             <0.001  \n",
       "MONO, mean (SD)                            0.4 (0.1)             <0.001  \n",
       "EOS, mean (SD)                             0.1 (0.1)             <0.001  \n",
       "BASO, mean (SD)                            0.0 (0.0)             <0.001  \n",
       "ALT, mean (SD)                           21.5 (22.3)             <0.001  \n",
       "AST, mean (SD)                           20.3 (15.9)              1.000  \n",
       "ALP, mean (SD)                           69.0 (20.0)             <0.001  \n",
       "ADA, mean (SD)                             8.8 (2.3)             <0.001  \n",
       "GPDA, mean (SD)                          78.4 (18.0)             <0.001  \n",
       "AFU, mean (SD)                            21.6 (5.4)             <0.001  \n",
       "T3, mean (SD)                              1.5 (0.3)             <0.001  \n",
       "T4, mean (SD)                            97.4 (16.8)             <0.001  \n",
       "TSH, mean (SD)                             1.9 (3.2)              1.000  \n",
       "FT4, mean (SD)                            13.4 (1.7)             <0.001  \n",
       "TPOAb, mean (SD)                        34.7 (143.9)              1.000  \n",
       "TBIL, mean (SD)                           11.7 (5.2)             <0.001  \n",
       "DBIL, mean (SD)                            4.2 (1.6)             <0.001  \n",
       "IBIL, mean (SD)                            7.5 (3.8)             <0.001  \n",
       "TBA, mean (SD)                             5.0 (4.6)             <0.001  \n",
       "Cr, mean (SD)                            72.0 (21.7)              1.000  \n",
       "HEART.Normal, n (%)             0.0     12063 (50.6)             <0.001  \n",
       "                                1.0     11775 (49.4)                     \n",
       "HEART.SinusRhythm, n (%)        0.0     17622 (73.9)              0.009  \n",
       "                                1.0      6216 (26.1)                     \n",
       "HEART.SinusBradycardia, n (%)   0.0     22381 (93.9)              0.001  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_table1plus_3p_revMM[\"HEART.Status\"] = df_table1plus_3p_revMM.apply(lambda x: get_heart_status(x), axis=1)\n",
    "df_sub = df_table1plus_3p_revMM[\n",
    "     l_basics+[\"period\"] + l_columns+l_category\n",
    "]\n",
    "\n",
    "l_cat_en = l_category[0:1] + list(df_meta_groups.loc[l_category[1:]][\"item_name_en\"])\n",
    "l_col_en = list(df_meta_groups.loc[l_columns][\"item_name_en\"])\n",
    "df_sub.columns = l_basics_en + [ \"period\"] + l_col_en + l_cat_en\n",
    "\n",
    "mytable = tableone.TableOne(df_sub, \n",
    "                            l_basics_en + l_col_en+l_cat_en,\n",
    "                            [\"gender\"]+l_cat_en, \n",
    "                            groupby=\"period\", \n",
    "                            pval=True, \n",
    "                            overall=False, missing=False, pval_adjust=\"bonferroni\")\n",
    "\n",
    "mytable.to_excel(f'{workdir}/TableS2.xlsx')\n",
    "mytable.head(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "907a7c53",
   "metadata": {
    "tags": []
   },
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">Grouped by period</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Control-2021</th>\n",
       "      <th>Control-2022</th>\n",
       "      <th>Test-2023</th>\n",
       "      <th>P-Value (adjusted)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>n</th>\n",
       "      <th></th>\n",
       "      <td>6786</td>\n",
       "      <td>6786</td>\n",
       "      <td>6786</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">gender, n (%)</th>\n",
       "      <th>female</th>\n",
       "      <td>4826 (71.1)</td>\n",
       "      <td>4826 (71.1)</td>\n",
       "      <td>4826 (71.1)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>1960 (28.9)</td>\n",
       "      <td>1960 (28.9)</td>\n",
       "      <td>1960 (28.9)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>37.5 (13.7)</td>\n",
       "      <td>38.5 (13.7)</td>\n",
       "      <td>39.5 (13.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>height, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>163.5 (7.7)</td>\n",
       "      <td>163.7 (7.7)</td>\n",
       "      <td>163.7 (7.7)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>59.6 (11.1)</td>\n",
       "      <td>60.3 (11.4)</td>\n",
       "      <td>60.3 (11.5)</td>\n",
       "      <td>0.089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>waist-circumference, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>85.1 (9.8)</td>\n",
       "      <td>84.6 (9.8)</td>\n",
       "      <td>84.6 (9.8)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HR, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>85.6 (12.8)</td>\n",
       "      <td>85.2 (12.3)</td>\n",
       "      <td>85.8 (12.2)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HCY, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>8.7 (4.3)</td>\n",
       "      <td>9.2 (3.7)</td>\n",
       "      <td>10.0 (4.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SBP, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>120.9 (15.7)</td>\n",
       "      <td>120.7 (15.5)</td>\n",
       "      <td>122.1 (15.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBP, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>71.6 (10.1)</td>\n",
       "      <td>71.7 (9.9)</td>\n",
       "      <td>72.9 (10.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TG, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.1 (0.9)</td>\n",
       "      <td>1.2 (1.1)</td>\n",
       "      <td>1.2 (0.9)</td>\n",
       "      <td>0.029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.5 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>4.7 (0.9)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HDL-C, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.4 (0.4)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>1.5 (0.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LDL-C, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>2.5 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>2.6 (0.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FPG, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.9 (0.8)</td>\n",
       "      <td>4.9 (0.8)</td>\n",
       "      <td>4.9 (0.9)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>6.8 (0.6)</td>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>7.0 (0.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1c, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>5.6 (0.5)</td>\n",
       "      <td>5.7 (0.8)</td>\n",
       "      <td>5.8 (0.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>55.2 (8.5)</td>\n",
       "      <td>53.9 (8.5)</td>\n",
       "      <td>54.4 (8.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>35.0 (7.9)</td>\n",
       "      <td>36.3 (8.0)</td>\n",
       "      <td>36.0 (7.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>7.1 (1.7)</td>\n",
       "      <td>7.0 (1.6)</td>\n",
       "      <td>6.8 (1.6)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.6 (0.3)</td>\n",
       "      <td>0.5 (0.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS%, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>2.1 (1.7)</td>\n",
       "      <td>2.2 (1.7)</td>\n",
       "      <td>2.3 (1.7)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.7 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>4.6 (0.5)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>246.9 (57.2)</td>\n",
       "      <td>250.5 (57.3)</td>\n",
       "      <td>254.3 (59.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WBC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>6.0 (1.5)</td>\n",
       "      <td>6.1 (1.5)</td>\n",
       "      <td>6.2 (1.6)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hb, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>139.5 (15.2)</td>\n",
       "      <td>138.7 (15.2)</td>\n",
       "      <td>137.5 (14.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hct, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>42.1 (4.0)</td>\n",
       "      <td>41.8 (4.0)</td>\n",
       "      <td>41.9 (4.1)</td>\n",
       "      <td>0.121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCV, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>90.2 (5.1)</td>\n",
       "      <td>90.2 (5.1)</td>\n",
       "      <td>90.8 (5.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCH, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>29.9 (2.2)</td>\n",
       "      <td>29.9 (2.1)</td>\n",
       "      <td>29.8 (2.1)</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCHC, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>331.4 (11.5)</td>\n",
       "      <td>331.5 (10.8)</td>\n",
       "      <td>327.7 (9.9)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RDW, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.6 (1.1)</td>\n",
       "      <td>12.9 (1.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPV, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>10.8 (1.0)</td>\n",
       "      <td>10.7 (1.0)</td>\n",
       "      <td>10.6 (1.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.3 (0.1)</td>\n",
       "      <td>0.423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>3.3 (1.2)</td>\n",
       "      <td>3.4 (1.2)</td>\n",
       "      <td>0.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>2.1 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>2.2 (0.6)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.4 (0.1)</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>0.1 (0.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>0.0 (0.0)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALT, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>18.1 (16.9)</td>\n",
       "      <td>19.0 (16.6)</td>\n",
       "      <td>20.1 (18.1)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AST, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>19.3 (10.5)</td>\n",
       "      <td>20.3 (9.8)</td>\n",
       "      <td>20.6 (8.8)</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALP, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>66.4 (19.3)</td>\n",
       "      <td>66.1 (19.3)</td>\n",
       "      <td>65.9 (19.1)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADA, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>8.5 (2.1)</td>\n",
       "      <td>8.2 (2.0)</td>\n",
       "      <td>8.8 (2.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GPDA, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>75.8 (15.8)</td>\n",
       "      <td>79.3 (17.6)</td>\n",
       "      <td>76.4 (17.4)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFU, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>20.3 (4.9)</td>\n",
       "      <td>20.4 (4.9)</td>\n",
       "      <td>21.6 (5.2)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T3, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.5 (0.3)</td>\n",
       "      <td>1.6 (0.3)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>99.4 (17.3)</td>\n",
       "      <td>98.8 (16.4)</td>\n",
       "      <td>99.9 (17.4)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSH, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>1.9 (2.9)</td>\n",
       "      <td>1.9 (1.4)</td>\n",
       "      <td>2.1 (6.0)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT4, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>13.4 (1.6)</td>\n",
       "      <td>13.4 (1.6)</td>\n",
       "      <td>13.8 (1.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TPOAb, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>41.3 (156.3)</td>\n",
       "      <td>38.5 (144.9)</td>\n",
       "      <td>44.3 (163.7)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBIL, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>11.1 (5.0)</td>\n",
       "      <td>11.0 (5.0)</td>\n",
       "      <td>11.0 (4.8)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBIL, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>4.0 (1.6)</td>\n",
       "      <td>3.9 (1.5)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBIL, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>7.2 (3.6)</td>\n",
       "      <td>7.0 (3.6)</td>\n",
       "      <td>7.0 (3.5)</td>\n",
       "      <td>0.072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBA, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>4.9 (11.0)</td>\n",
       "      <td>5.1 (8.9)</td>\n",
       "      <td>5.3 (4.8)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cr, mean (SD)</th>\n",
       "      <th></th>\n",
       "      <td>67.4 (18.5)</td>\n",
       "      <td>66.2 (19.2)</td>\n",
       "      <td>65.4 (18.8)</td>\n",
       "      <td>&lt;0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">HEART.Normal, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>2904 (42.8)</td>\n",
       "      <td>2978 (43.9)</td>\n",
       "      <td>3171 (46.7)</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>3882 (57.2)</td>\n",
       "      <td>3808 (56.1)</td>\n",
       "      <td>3615 (53.3)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">HEART.SinusRhythm, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>5297 (78.1)</td>\n",
       "      <td>5201 (76.6)</td>\n",
       "      <td>5103 (75.2)</td>\n",
       "      <td>0.033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>1489 (21.9)</td>\n",
       "      <td>1585 (23.4)</td>\n",
       "      <td>1683 (24.8)</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEART.SinusBradycardia, n (%)</th>\n",
       "      <th>0.0</th>\n",
       "      <td>6528 (96.2)</td>\n",
       "      <td>6492 (95.7)</td>\n",
       "      <td>6547 (96.5)</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       Grouped by period                \\\n",
       "                                            Control-2021  Control-2022   \n",
       "n                                                   6786          6786   \n",
       "gender, n (%)                   female       4826 (71.1)   4826 (71.1)   \n",
       "                                male         1960 (28.9)   1960 (28.9)   \n",
       "age, mean (SD)                               37.5 (13.7)   38.5 (13.7)   \n",
       "height, mean (SD)                            163.5 (7.7)   163.7 (7.7)   \n",
       "weight, mean (SD)                            59.6 (11.1)   60.3 (11.4)   \n",
       " waist-circumference, mean (SD)               85.1 (9.8)    84.6 (9.8)   \n",
       "HR, mean (SD)                                85.6 (12.8)   85.2 (12.3)   \n",
       "HCY, mean (SD)                                 8.7 (4.3)     9.2 (3.7)   \n",
       "SBP, mean (SD)                              120.9 (15.7)  120.7 (15.5)   \n",
       "DBP, mean (SD)                               71.6 (10.1)    71.7 (9.9)   \n",
       "TG, mean (SD)                                  1.1 (0.9)     1.2 (1.1)   \n",
       "TC, mean (SD)                                  4.5 (0.9)     4.7 (0.9)   \n",
       "HDL-C, mean (SD)                               1.4 (0.4)     1.5 (0.4)   \n",
       "LDL-C, mean (SD)                               2.5 (0.7)     2.6 (0.7)   \n",
       "FPG, mean (SD)                                 4.9 (0.8)     4.9 (0.8)   \n",
       "HbA1, mean (SD)                                6.8 (0.6)     7.0 (0.8)   \n",
       "HbA1c, mean (SD)                               5.6 (0.5)     5.7 (0.8)   \n",
       "NEUT%, mean (SD)                              55.2 (8.5)    53.9 (8.5)   \n",
       "LYMPH%, mean (SD)                             35.0 (7.9)    36.3 (8.0)   \n",
       "MONO%, mean (SD)                               7.1 (1.7)     7.0 (1.6)   \n",
       "BASO%, mean (SD)                               0.6 (0.3)     0.6 (0.3)   \n",
       "EOS%, mean (SD)                                2.1 (1.7)     2.2 (1.7)   \n",
       "RBC, mean (SD)                                 4.7 (0.5)     4.6 (0.5)   \n",
       "PLT, mean (SD)                              246.9 (57.2)  250.5 (57.3)   \n",
       "WBC, mean (SD)                                 6.0 (1.5)     6.1 (1.5)   \n",
       "Hb, mean (SD)                               139.5 (15.2)  138.7 (15.2)   \n",
       "Hct, mean (SD)                                42.1 (4.0)    41.8 (4.0)   \n",
       "MCV, mean (SD)                                90.2 (5.1)    90.2 (5.1)   \n",
       "MCH, mean (SD)                                29.9 (2.2)    29.9 (2.1)   \n",
       "MCHC, mean (SD)                             331.4 (11.5)  331.5 (10.8)   \n",
       "RDW, mean (SD)                                12.6 (1.1)    12.6 (1.1)   \n",
       "MPV, mean (SD)                                10.8 (1.0)    10.7 (1.0)   \n",
       "PCT, mean (SD)                                 0.3 (0.1)     0.3 (0.1)   \n",
       "NEUT, mean (SD)                                3.4 (1.2)     3.3 (1.2)   \n",
       "LYMPH, mean (SD)                               2.1 (0.6)     2.2 (0.6)   \n",
       "MONO, mean (SD)                                0.4 (0.1)     0.4 (0.1)   \n",
       "EOS, mean (SD)                                 0.1 (0.1)     0.1 (0.1)   \n",
       "BASO, mean (SD)                                0.0 (0.0)     0.0 (0.0)   \n",
       "ALT, mean (SD)                               18.1 (16.9)   19.0 (16.6)   \n",
       "AST, mean (SD)                               19.3 (10.5)    20.3 (9.8)   \n",
       "ALP, mean (SD)                               66.4 (19.3)   66.1 (19.3)   \n",
       "ADA, mean (SD)                                 8.5 (2.1)     8.2 (2.0)   \n",
       "GPDA, mean (SD)                              75.8 (15.8)   79.3 (17.6)   \n",
       "AFU, mean (SD)                                20.3 (4.9)    20.4 (4.9)   \n",
       "T3, mean (SD)                                  1.5 (0.3)     1.5 (0.3)   \n",
       "T4, mean (SD)                                99.4 (17.3)   98.8 (16.4)   \n",
       "TSH, mean (SD)                                 1.9 (2.9)     1.9 (1.4)   \n",
       "FT4, mean (SD)                                13.4 (1.6)    13.4 (1.6)   \n",
       "TPOAb, mean (SD)                            41.3 (156.3)  38.5 (144.9)   \n",
       "TBIL, mean (SD)                               11.1 (5.0)    11.0 (5.0)   \n",
       "DBIL, mean (SD)                                3.9 (1.5)     4.0 (1.6)   \n",
       "IBIL, mean (SD)                                7.2 (3.6)     7.0 (3.6)   \n",
       "TBA, mean (SD)                                4.9 (11.0)     5.1 (8.9)   \n",
       "Cr, mean (SD)                                67.4 (18.5)   66.2 (19.2)   \n",
       "HEART.Normal, n (%)             0.0          2904 (42.8)   2978 (43.9)   \n",
       "                                1.0          3882 (57.2)   3808 (56.1)   \n",
       "HEART.SinusRhythm, n (%)        0.0          5297 (78.1)   5201 (76.6)   \n",
       "                                1.0          1489 (21.9)   1585 (23.4)   \n",
       "HEART.SinusBradycardia, n (%)   0.0          6528 (96.2)   6492 (95.7)   \n",
       "\n",
       "                                                                         \n",
       "                                           Test-2023 P-Value (adjusted)  \n",
       "n                                               6786                     \n",
       "gender, n (%)                   female   4826 (71.1)              1.000  \n",
       "                                male     1960 (28.9)                     \n",
       "age, mean (SD)                           39.5 (13.7)             <0.001  \n",
       "height, mean (SD)                        163.7 (7.7)              1.000  \n",
       "weight, mean (SD)                        60.3 (11.5)              0.089  \n",
       " waist-circumference, mean (SD)           84.6 (9.8)              1.000  \n",
       "HR, mean (SD)                            85.8 (12.2)              1.000  \n",
       "HCY, mean (SD)                            10.0 (4.0)             <0.001  \n",
       "SBP, mean (SD)                          122.1 (15.7)             <0.001  \n",
       "DBP, mean (SD)                           72.9 (10.0)             <0.001  \n",
       "TG, mean (SD)                              1.2 (0.9)              0.029  \n",
       "TC, mean (SD)                              4.7 (0.9)             <0.001  \n",
       "HDL-C, mean (SD)                           1.5 (0.4)             <0.001  \n",
       "LDL-C, mean (SD)                           2.6 (0.7)             <0.001  \n",
       "FPG, mean (SD)                             4.9 (0.9)              1.000  \n",
       "HbA1, mean (SD)                            7.0 (0.8)             <0.001  \n",
       "HbA1c, mean (SD)                           5.8 (0.7)             <0.001  \n",
       "NEUT%, mean (SD)                          54.4 (8.2)             <0.001  \n",
       "LYMPH%, mean (SD)                         36.0 (7.7)             <0.001  \n",
       "MONO%, mean (SD)                           6.8 (1.6)             <0.001  \n",
       "BASO%, mean (SD)                           0.5 (0.3)             <0.001  \n",
       "EOS%, mean (SD)                            2.3 (1.7)             <0.001  \n",
       "RBC, mean (SD)                             4.6 (0.5)             <0.001  \n",
       "PLT, mean (SD)                          254.3 (59.3)             <0.001  \n",
       "WBC, mean (SD)                             6.2 (1.6)             <0.001  \n",
       "Hb, mean (SD)                           137.5 (14.8)             <0.001  \n",
       "Hct, mean (SD)                            41.9 (4.1)              0.121  \n",
       "MCV, mean (SD)                            90.8 (5.2)             <0.001  \n",
       "MCH, mean (SD)                            29.8 (2.1)              0.001  \n",
       "MCHC, mean (SD)                          327.7 (9.9)             <0.001  \n",
       "RDW, mean (SD)                            12.9 (1.1)             <0.001  \n",
       "MPV, mean (SD)                            10.6 (1.0)             <0.001  \n",
       "PCT, mean (SD)                             0.3 (0.1)              0.423  \n",
       "NEUT, mean (SD)                            3.4 (1.2)              0.073  \n",
       "LYMPH, mean (SD)                           2.2 (0.6)             <0.001  \n",
       "MONO, mean (SD)                            0.4 (0.1)              0.001  \n",
       "EOS, mean (SD)                             0.1 (0.1)             <0.001  \n",
       "BASO, mean (SD)                            0.0 (0.0)             <0.001  \n",
       "ALT, mean (SD)                           20.1 (18.1)             <0.001  \n",
       "AST, mean (SD)                            20.6 (8.8)              0.005  \n",
       "ALP, mean (SD)                           65.9 (19.1)              1.000  \n",
       "ADA, mean (SD)                             8.8 (2.3)             <0.001  \n",
       "GPDA, mean (SD)                          76.4 (17.4)             <0.001  \n",
       "AFU, mean (SD)                            21.6 (5.2)             <0.001  \n",
       "T3, mean (SD)                              1.6 (0.3)             <0.001  \n",
       "T4, mean (SD)                            99.9 (17.4)              1.000  \n",
       "TSH, mean (SD)                             2.1 (6.0)              1.000  \n",
       "FT4, mean (SD)                            13.8 (1.8)             <0.001  \n",
       "TPOAb, mean (SD)                        44.3 (163.7)              1.000  \n",
       "TBIL, mean (SD)                           11.0 (4.8)              1.000  \n",
       "DBIL, mean (SD)                            3.9 (1.5)              1.000  \n",
       "IBIL, mean (SD)                            7.0 (3.5)              0.072  \n",
       "TBA, mean (SD)                             5.3 (4.8)              1.000  \n",
       "Cr, mean (SD)                            65.4 (18.8)             <0.001  \n",
       "HEART.Normal, n (%)             0.0      3171 (46.7)              0.001  \n",
       "                                1.0      3615 (53.3)                     \n",
       "HEART.SinusRhythm, n (%)        0.0      5103 (75.2)              0.033  \n",
       "                                1.0      1683 (24.8)                     \n",
       "HEART.SinusBradycardia, n (%)   0.0      6547 (96.5)              1.000  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_table1plus_3p_revMM[\"HEART.Status\"] = df_table1plus_3p_revMM.apply(lambda x: get_heart_status(x), axis=1)\n",
    "df_sub = df_table1plus_3p_revMM[df_table1plus_3p_revMM[\"month\"].isin([12,1,2])][\n",
    "     l_basics+[\"period\"] + l_columns+l_category\n",
    "]\n",
    "\n",
    "l_cat_en = l_category[0:1] + list(df_meta_groups.loc[l_category[1:]][\"item_name_en\"])\n",
    "l_col_en = list(df_meta_groups.loc[l_columns][\"item_name_en\"])\n",
    "df_sub.columns = l_basics_en + [ \"period\"] + l_col_en + l_cat_en\n",
    "\n",
    "mytable = tableone.TableOne(df_sub, \n",
    "                            l_basics_en + l_col_en+l_cat_en,\n",
    "                            [\"gender\"]+l_cat_en, \n",
    "                            groupby=\"period\", \n",
    "                            pval=True, \n",
    "                            overall=False, missing=False, pval_adjust=\"bonferroni\")\n",
    "mytable.to_excel(f'{workdir}/TableS3.xlsx')\n",
    "mytable.head(60)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "070890f3-9195-4a8b-a057-1a3c52bfa437",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_table_one_months(df_table1plus_3p_revMM, l_months=[12,1,2]):\n",
    "    df_sub = df_table1plus_3p_revMM[df_table1plus_3p_revMM[\"month\"].isin(l_months)][\n",
    "         l_basics+[\"period\"] + l_columns+l_category\n",
    "    ]\n",
    "\n",
    "    l_cat_en = l_category[0:1] + list(df_meta_groups.loc[l_category[1:]][\"item_name_en\"])\n",
    "    l_col_en = list(df_meta_groups.loc[l_columns][\"item_name_en\"])\n",
    "    df_sub.columns = l_basics_en + [ \"period\"] + l_col_en + l_cat_en\n",
    "\n",
    "    mytable = tableone.TableOne(df_sub, \n",
    "                                l_basics_en + l_col_en+l_cat_en,\n",
    "                                [\"gender\"]+l_cat_en, \n",
    "                                groupby=\"period\", \n",
    "                                pval=True, \n",
    "                                overall=False, missing=False, pval_adjust=\"bonferroni\")\n",
    "    return mytable\n",
    "\n",
    "my_table_pre = get_table_one_months(df_table1plus_3p_revMM, l_months=[11])\n",
    "my_table_ = get_table_one_months(df_table1plus_3p_revMM, l_months=[12,1,2])\n",
    "my_table_after = get_table_one_months(df_table1plus_3p_revMM, l_months=[3,4,5,6])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "35e17bc0-2010-4e8d-a554-39ac20124ec8",
   "metadata": {
    "tags": []
   },
   "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>items</th>\n",
       "      <th>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>height</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>1.000404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>weight</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>1.003826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>waist-circumference</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>0.986614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HR</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>0.989598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HCY</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>0.986015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>TBIL</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>0.973466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>DBIL</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>0.975301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>IBIL</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>0.972114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>TBA</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>1.113135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Cr</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>1.010697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>153 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    items                                           variable  \\\n",
       "0                  height             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "1                  weight             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "2     waist-circumference             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "3                      HR             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "4                     HCY             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "..                    ...                                                ...   \n",
       "148                  TBIL  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "149                  DBIL  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "150                  IBIL  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "151                   TBA  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "152                    Cr  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "\n",
       "        value  \n",
       "0    1.000404  \n",
       "1    1.003826  \n",
       "2    0.986614  \n",
       "3    0.989598  \n",
       "4    0.986015  \n",
       "..        ...  \n",
       "148  0.973466  \n",
       "149  0.975301  \n",
       "150  0.972114  \n",
       "151  1.113135  \n",
       "152  1.010697  \n",
       "\n",
       "[153 rows x 3 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_ratio(my_table):\n",
    "    df_mean = my_table.cont_describe[\"mean\"]\n",
    "    np_ratio = df_mean.apply(lambda x: 2*x[\"Test-2023\"] / (x[\"Control-2021\"]+x[\"Control-2022\"]), axis=1)\n",
    "    return np_ratio#.reset_index()\n",
    "\n",
    "df_res = get_ratio(my_table_pre).reset_index()\n",
    "l_hue_orders = [\"2022Nov vs mean of 2020Nov and 2021Nov\", \"2022Dec~2023Feb vs mean of 2021Dec~2022Feb and 2020Dec~2021Feb\", \"2023Mar~2023Jun vs mean of 2022Mar~2022Jun and 2021Mar~2021Jun\"]\n",
    "df_res.columns = [\"items\", l_hue_orders[0]]\n",
    "df_res[l_hue_orders[1]] = get_ratio(my_table_).values\n",
    "df_res[l_hue_orders[2]] = get_ratio(my_table_after).values\n",
    "df_res.index = list(df_res[\"items\"])\n",
    "l_tags = l_basics_en[2:]+l_col_en\n",
    "df_ratio = pd.melt(df_res.loc[l_tags], id_vars=\"items\")\n",
    "df_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f76ee395-19a0-4db7-8c6d-c6c7b0b47f34",
   "metadata": {
    "tags": []
   },
   "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>Control-2021</th>\n",
       "      <th>Control-2022</th>\n",
       "      <th>Test-2023</th>\n",
       "      <th>Missing</th>\n",
       "      <th>P-Value (adjusted)</th>\n",
       "      <th>Test</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</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></th>\n",
       "      <td>4.4 (3.1)</td>\n",
       "      <td>4.6 (3.2)</td>\n",
       "      <td>4.5 (3.3)</td>\n",
       "      <td>4512</td>\n",
       "      <td>1</td>\n",
       "      <td>One-way ANOVA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>4.9 (11.0)</td>\n",
       "      <td>5.1 (8.9)</td>\n",
       "      <td>5.3 (4.8)</td>\n",
       "      <td>14908</td>\n",
       "      <td>1</td>\n",
       "      <td>One-way ANOVA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <td>4.3 (4.1)</td>\n",
       "      <td>4.6 (4.1)</td>\n",
       "      <td>4.9 (4.7)</td>\n",
       "      <td>18296</td>\n",
       "      <td>0.0</td>\n",
       "      <td>One-way ANOVA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Control-2021 Control-2022  Test-2023  Missing P-Value (adjusted)  \\\n",
       "value                                                                    \n",
       "         4.4 (3.1)    4.6 (3.2)  4.5 (3.3)     4512                  1   \n",
       "        4.9 (11.0)    5.1 (8.9)  5.3 (4.8)    14908                  1   \n",
       "         4.3 (4.1)    4.6 (4.1)  4.9 (4.7)    18296                0.0   \n",
       "\n",
       "                Test  \n",
       "value                 \n",
       "       One-way ANOVA  \n",
       "       One-way ANOVA  \n",
       "       One-way ANOVA  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df_res.loc[\"HCY\"]\n",
    "tagn = \"HCY\"\n",
    "tagn = \"TBA\"\n",
    "pd.concat([\n",
    "    my_table_pre.cont_table.loc[tagn],\n",
    "    my_table_.cont_table.loc[tagn],\n",
    "    my_table_after.cont_table.loc[tagn],\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b37e064d-9786-4998-87f5-1bb0334aca50",
   "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>items</th>\n",
       "      <th>variable</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>height</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>1.000404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>weight</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>1.003826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>waist-circumference</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>0.986614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HR</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>0.989598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HCY</td>\n",
       "      <td>2022Nov vs mean of 2020Nov and 2021Nov</td>\n",
       "      <td>0.986015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>TBIL</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>0.973466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>DBIL</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>0.975301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>IBIL</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>0.972114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>TBA</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>1.113135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Cr</td>\n",
       "      <td>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...</td>\n",
       "      <td>1.010697</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>153 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    items                                           variable  \\\n",
       "0                  height             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "1                  weight             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "2     waist-circumference             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "3                      HR             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "4                     HCY             2022Nov vs mean of 2020Nov and 2021Nov   \n",
       "..                    ...                                                ...   \n",
       "148                  TBIL  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "149                  DBIL  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "150                  IBIL  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "151                   TBA  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "152                    Cr  2023Mar~2023Jun vs mean of 2022Mar~2022Jun and...   \n",
       "\n",
       "        value  \n",
       "0    1.000404  \n",
       "1    1.003826  \n",
       "2    0.986614  \n",
       "3    0.989598  \n",
       "4    0.986015  \n",
       "..        ...  \n",
       "148  0.973466  \n",
       "149  0.975301  \n",
       "150  0.972114  \n",
       "151  1.113135  \n",
       "152  1.010697  \n",
       "\n",
       "[153 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55ffcbf9-2b6a-411c-a70c-3dfc059c0e48",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca1515a1-1b5e-4340-8abd-94a96c02a9ce",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ea67deb1-faa6-4a44-b7e1-656aa905711d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_pal = [\"#0172B6\", \"#BD3C29\", \"#fb8072\"]\n",
    "fig = plt.figure(figsize=(9,3))\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "sns.barplot(data=df_ratio, x=\"items\", y=\"value\", hue=\"variable\", hue_order=l_hue_orders, palette=my_pal, ax=ax)\n",
    "ax.set_ylim((0.85, 1.15))\n",
    "ax.set_xlim((-1, len(l_tags)))\n",
    "ax.hlines(0.9, -1, 100, linestyles=\"dashed\", color=\"#888888\")\n",
    "ax.hlines(1.0, -1, 100, linestyles=\"dashed\", color=\"#555555\")\n",
    "ax.hlines(1.1, -1, 100, linestyles=\"dashed\", color=\"#888888\")\n",
    "ax.set_xticks(np.arange(len(l_tags)))\n",
    "ax.set_xticklabels(l_tags, rotation=90)\n",
    "ax.set_title(\"\")\n",
    "ax.set_ylabel(\"ratio\")\n",
    "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "fig.savefig(f\"{workdir}/figures/Figure1_G.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "dee78efc-9cfa-4b98-8d98-58d62a800244",
   "metadata": {
    "tags": []
   },
   "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>items</th>\n",
       "      <th>2022Nov vs mean of 2020Nov and 2021Nov</th>\n",
       "      <th>2022Dec~2023Feb vs mean of 2021Dec~2022Feb and 2020Dec~2021Feb</th>\n",
       "      <th>2023Mar~2023Jun vs mean of 2022Mar~2022Jun and 2021Mar~2021Jun</th>\n",
       "      <th>variable_p</th>\n",
       "      <th>ratio_pre_p</th>\n",
       "      <th>ratio_now_p</th>\n",
       "      <th>ratio_after_p</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>waist-circumference</th>\n",
       "      <td>waist-circumference</td>\n",
       "      <td>0.986614</td>\n",
       "      <td>0.997342</td>\n",
       "      <td>0.994662</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADA</th>\n",
       "      <td>ADA</td>\n",
       "      <td>1.005045</td>\n",
       "      <td>1.046310</td>\n",
       "      <td>1.053452</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFU</th>\n",
       "      <td>AFU</td>\n",
       "      <td>1.058023</td>\n",
       "      <td>1.058907</td>\n",
       "      <td>1.048839</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALP</th>\n",
       "      <td>ALP</td>\n",
       "      <td>0.997434</td>\n",
       "      <td>0.994297</td>\n",
       "      <td>0.974872</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALT</th>\n",
       "      <td>ALT</td>\n",
       "      <td>1.020155</td>\n",
       "      <td>1.082640</td>\n",
       "      <td>1.025062</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AST</th>\n",
       "      <td>AST</td>\n",
       "      <td>0.999277</td>\n",
       "      <td>1.041641</td>\n",
       "      <td>1.011981</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO</th>\n",
       "      <td>BASO</td>\n",
       "      <td>0.935133</td>\n",
       "      <td>0.956607</td>\n",
       "      <td>0.963598</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO%</th>\n",
       "      <td>BASO%</td>\n",
       "      <td>0.935283</td>\n",
       "      <td>0.939071</td>\n",
       "      <td>0.954259</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cr</th>\n",
       "      <td>Cr</td>\n",
       "      <td>1.000220</td>\n",
       "      <td>0.978864</td>\n",
       "      <td>1.010697</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBIL</th>\n",
       "      <td>DBIL</td>\n",
       "      <td>1.017727</td>\n",
       "      <td>0.997501</td>\n",
       "      <td>0.975301</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBP</th>\n",
       "      <td>DBP</td>\n",
       "      <td>1.003748</td>\n",
       "      <td>1.017757</td>\n",
       "      <td>1.016458</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS</th>\n",
       "      <td>EOS</td>\n",
       "      <td>1.022074</td>\n",
       "      <td>1.070589</td>\n",
       "      <td>1.034703</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS%</th>\n",
       "      <td>EOS%</td>\n",
       "      <td>1.017399</td>\n",
       "      <td>1.048277</td>\n",
       "      <td>1.023678</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FPG</th>\n",
       "      <td>FPG</td>\n",
       "      <td>0.971768</td>\n",
       "      <td>0.994823</td>\n",
       "      <td>0.996600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT4</th>\n",
       "      <td>FT4</td>\n",
       "      <td>0.998594</td>\n",
       "      <td>1.026793</td>\n",
       "      <td>1.016128</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GPDA</th>\n",
       "      <td>GPDA</td>\n",
       "      <td>1.003215</td>\n",
       "      <td>0.984638</td>\n",
       "      <td>0.988741</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HCY</th>\n",
       "      <td>HCY</td>\n",
       "      <td>0.986015</td>\n",
       "      <td>1.113978</td>\n",
       "      <td>1.082360</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HDL-C</th>\n",
       "      <td>HDL-C</td>\n",
       "      <td>1.029705</td>\n",
       "      <td>1.002250</td>\n",
       "      <td>0.995797</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HR</th>\n",
       "      <td>HR</td>\n",
       "      <td>0.989598</td>\n",
       "      <td>1.004336</td>\n",
       "      <td>0.999423</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hb</th>\n",
       "      <td>Hb</td>\n",
       "      <td>0.990927</td>\n",
       "      <td>0.988506</td>\n",
       "      <td>0.990830</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1</th>\n",
       "      <td>HbA1</td>\n",
       "      <td>0.997914</td>\n",
       "      <td>1.018285</td>\n",
       "      <td>1.022070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1c</th>\n",
       "      <td>HbA1c</td>\n",
       "      <td>0.990936</td>\n",
       "      <td>1.018271</td>\n",
       "      <td>1.024176</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hct</th>\n",
       "      <td>Hct</td>\n",
       "      <td>1.004266</td>\n",
       "      <td>0.999883</td>\n",
       "      <td>0.997368</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBIL</th>\n",
       "      <td>IBIL</td>\n",
       "      <td>0.971511</td>\n",
       "      <td>0.988671</td>\n",
       "      <td>0.972114</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LDL-C</th>\n",
       "      <td>LDL-C</td>\n",
       "      <td>0.996630</td>\n",
       "      <td>1.036263</td>\n",
       "      <td>0.999032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH</th>\n",
       "      <td>LYMPH</td>\n",
       "      <td>1.019663</td>\n",
       "      <td>1.031419</td>\n",
       "      <td>1.030862</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH%</th>\n",
       "      <td>LYMPH%</td>\n",
       "      <td>1.017746</td>\n",
       "      <td>1.009320</td>\n",
       "      <td>1.016692</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCH</th>\n",
       "      <td>MCH</td>\n",
       "      <td>0.995612</td>\n",
       "      <td>0.994939</td>\n",
       "      <td>0.994454</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCHC</th>\n",
       "      <td>MCHC</td>\n",
       "      <td>0.986886</td>\n",
       "      <td>0.988797</td>\n",
       "      <td>0.993479</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCV</th>\n",
       "      <td>MCV</td>\n",
       "      <td>1.008937</td>\n",
       "      <td>1.006251</td>\n",
       "      <td>1.001063</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO</th>\n",
       "      <td>MONO</td>\n",
       "      <td>0.945082</td>\n",
       "      <td>0.978687</td>\n",
       "      <td>0.998584</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO%</th>\n",
       "      <td>MONO%</td>\n",
       "      <td>0.941492</td>\n",
       "      <td>0.960534</td>\n",
       "      <td>0.987486</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPV</th>\n",
       "      <td>MPV</td>\n",
       "      <td>0.985415</td>\n",
       "      <td>0.981920</td>\n",
       "      <td>0.980902</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT</th>\n",
       "      <td>NEUT</td>\n",
       "      <td>0.994821</td>\n",
       "      <td>1.013358</td>\n",
       "      <td>1.002433</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT%</th>\n",
       "      <td>NEUT%</td>\n",
       "      <td>0.996629</td>\n",
       "      <td>0.997737</td>\n",
       "      <td>0.990619</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCT</th>\n",
       "      <td>PCT</td>\n",
       "      <td>0.990546</td>\n",
       "      <td>1.003904</td>\n",
       "      <td>0.997175</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLT</th>\n",
       "      <td>PLT</td>\n",
       "      <td>1.003585</td>\n",
       "      <td>1.022476</td>\n",
       "      <td>1.016716</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBC</th>\n",
       "      <td>RBC</td>\n",
       "      <td>0.995350</td>\n",
       "      <td>0.993603</td>\n",
       "      <td>0.996283</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RDW</th>\n",
       "      <td>RDW</td>\n",
       "      <td>1.006403</td>\n",
       "      <td>1.022395</td>\n",
       "      <td>1.010126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SBP</th>\n",
       "      <td>SBP</td>\n",
       "      <td>1.004334</td>\n",
       "      <td>1.010808</td>\n",
       "      <td>1.014004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T3</th>\n",
       "      <td>T3</td>\n",
       "      <td>1.032981</td>\n",
       "      <td>1.070384</td>\n",
       "      <td>0.998174</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4</th>\n",
       "      <td>T4</td>\n",
       "      <td>1.019868</td>\n",
       "      <td>1.008279</td>\n",
       "      <td>1.010895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBA</th>\n",
       "      <td>TBA</td>\n",
       "      <td>0.987351</td>\n",
       "      <td>1.066072</td>\n",
       "      <td>1.113135</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBIL</th>\n",
       "      <td>TBIL</td>\n",
       "      <td>0.987727</td>\n",
       "      <td>0.991726</td>\n",
       "      <td>0.973466</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TC</th>\n",
       "      <td>TC</td>\n",
       "      <td>1.019183</td>\n",
       "      <td>1.027388</td>\n",
       "      <td>1.005610</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TG</th>\n",
       "      <td>TG</td>\n",
       "      <td>1.029933</td>\n",
       "      <td>1.027639</td>\n",
       "      <td>1.022233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TPOAb</th>\n",
       "      <td>TPOAb</td>\n",
       "      <td>1.074530</td>\n",
       "      <td>1.111281</td>\n",
       "      <td>1.087736</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSH</th>\n",
       "      <td>TSH</td>\n",
       "      <td>1.003452</td>\n",
       "      <td>1.075401</td>\n",
       "      <td>0.970637</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WBC</th>\n",
       "      <td>WBC</td>\n",
       "      <td>0.999849</td>\n",
       "      <td>1.018224</td>\n",
       "      <td>1.012516</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>age</td>\n",
       "      <td>1.035074</td>\n",
       "      <td>1.039424</td>\n",
       "      <td>1.032227</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>height</th>\n",
       "      <td>height</td>\n",
       "      <td>1.000404</td>\n",
       "      <td>1.000750</td>\n",
       "      <td>1.000251</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight</th>\n",
       "      <td>weight</td>\n",
       "      <td>1.003826</td>\n",
       "      <td>1.004826</td>\n",
       "      <td>1.002197</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     items  \\\n",
       " waist-circumference   waist-circumference   \n",
       "ADA                                    ADA   \n",
       "AFU                                    AFU   \n",
       "ALP                                    ALP   \n",
       "ALT                                    ALT   \n",
       "AST                                    AST   \n",
       "BASO                                  BASO   \n",
       "BASO%                                BASO%   \n",
       "Cr                                      Cr   \n",
       "DBIL                                  DBIL   \n",
       "DBP                                    DBP   \n",
       "EOS                                    EOS   \n",
       "EOS%                                  EOS%   \n",
       "FPG                                    FPG   \n",
       "FT4                                    FT4   \n",
       "GPDA                                  GPDA   \n",
       "HCY                                    HCY   \n",
       "HDL-C                                HDL-C   \n",
       "HR                                      HR   \n",
       "Hb                                      Hb   \n",
       "HbA1                                  HbA1   \n",
       "HbA1c                                HbA1c   \n",
       "Hct                                    Hct   \n",
       "IBIL                                  IBIL   \n",
       "LDL-C                                LDL-C   \n",
       "LYMPH                                LYMPH   \n",
       "LYMPH%                              LYMPH%   \n",
       "MCH                                    MCH   \n",
       "MCHC                                  MCHC   \n",
       "MCV                                    MCV   \n",
       "MONO                                  MONO   \n",
       "MONO%                                MONO%   \n",
       "MPV                                    MPV   \n",
       "NEUT                                  NEUT   \n",
       "NEUT%                                NEUT%   \n",
       "PCT                                    PCT   \n",
       "PLT                                    PLT   \n",
       "RBC                                    RBC   \n",
       "RDW                                    RDW   \n",
       "SBP                                    SBP   \n",
       "T3                                      T3   \n",
       "T4                                      T4   \n",
       "TBA                                    TBA   \n",
       "TBIL                                  TBIL   \n",
       "TC                                      TC   \n",
       "TG                                      TG   \n",
       "TPOAb                                TPOAb   \n",
       "TSH                                    TSH   \n",
       "WBC                                    WBC   \n",
       "age                                    age   \n",
       "height                              height   \n",
       "weight                              weight   \n",
       "\n",
       "                      2022Nov vs mean of 2020Nov and 2021Nov  \\\n",
       " waist-circumference                                0.986614   \n",
       "ADA                                                 1.005045   \n",
       "AFU                                                 1.058023   \n",
       "ALP                                                 0.997434   \n",
       "ALT                                                 1.020155   \n",
       "AST                                                 0.999277   \n",
       "BASO                                                0.935133   \n",
       "BASO%                                               0.935283   \n",
       "Cr                                                  1.000220   \n",
       "DBIL                                                1.017727   \n",
       "DBP                                                 1.003748   \n",
       "EOS                                                 1.022074   \n",
       "EOS%                                                1.017399   \n",
       "FPG                                                 0.971768   \n",
       "FT4                                                 0.998594   \n",
       "GPDA                                                1.003215   \n",
       "HCY                                                 0.986015   \n",
       "HDL-C                                               1.029705   \n",
       "HR                                                  0.989598   \n",
       "Hb                                                  0.990927   \n",
       "HbA1                                                0.997914   \n",
       "HbA1c                                               0.990936   \n",
       "Hct                                                 1.004266   \n",
       "IBIL                                                0.971511   \n",
       "LDL-C                                               0.996630   \n",
       "LYMPH                                               1.019663   \n",
       "LYMPH%                                              1.017746   \n",
       "MCH                                                 0.995612   \n",
       "MCHC                                                0.986886   \n",
       "MCV                                                 1.008937   \n",
       "MONO                                                0.945082   \n",
       "MONO%                                               0.941492   \n",
       "MPV                                                 0.985415   \n",
       "NEUT                                                0.994821   \n",
       "NEUT%                                               0.996629   \n",
       "PCT                                                 0.990546   \n",
       "PLT                                                 1.003585   \n",
       "RBC                                                 0.995350   \n",
       "RDW                                                 1.006403   \n",
       "SBP                                                 1.004334   \n",
       "T3                                                  1.032981   \n",
       "T4                                                  1.019868   \n",
       "TBA                                                 0.987351   \n",
       "TBIL                                                0.987727   \n",
       "TC                                                  1.019183   \n",
       "TG                                                  1.029933   \n",
       "TPOAb                                               1.074530   \n",
       "TSH                                                 1.003452   \n",
       "WBC                                                 0.999849   \n",
       "age                                                 1.035074   \n",
       "height                                              1.000404   \n",
       "weight                                              1.003826   \n",
       "\n",
       "                      2022Dec~2023Feb vs mean of 2021Dec~2022Feb and 2020Dec~2021Feb  \\\n",
       " waist-circumference                                           0.997342                \n",
       "ADA                                                            1.046310                \n",
       "AFU                                                            1.058907                \n",
       "ALP                                                            0.994297                \n",
       "ALT                                                            1.082640                \n",
       "AST                                                            1.041641                \n",
       "BASO                                                           0.956607                \n",
       "BASO%                                                          0.939071                \n",
       "Cr                                                             0.978864                \n",
       "DBIL                                                           0.997501                \n",
       "DBP                                                            1.017757                \n",
       "EOS                                                            1.070589                \n",
       "EOS%                                                           1.048277                \n",
       "FPG                                                            0.994823                \n",
       "FT4                                                            1.026793                \n",
       "GPDA                                                           0.984638                \n",
       "HCY                                                            1.113978                \n",
       "HDL-C                                                          1.002250                \n",
       "HR                                                             1.004336                \n",
       "Hb                                                             0.988506                \n",
       "HbA1                                                           1.018285                \n",
       "HbA1c                                                          1.018271                \n",
       "Hct                                                            0.999883                \n",
       "IBIL                                                           0.988671                \n",
       "LDL-C                                                          1.036263                \n",
       "LYMPH                                                          1.031419                \n",
       "LYMPH%                                                         1.009320                \n",
       "MCH                                                            0.994939                \n",
       "MCHC                                                           0.988797                \n",
       "MCV                                                            1.006251                \n",
       "MONO                                                           0.978687                \n",
       "MONO%                                                          0.960534                \n",
       "MPV                                                            0.981920                \n",
       "NEUT                                                           1.013358                \n",
       "NEUT%                                                          0.997737                \n",
       "PCT                                                            1.003904                \n",
       "PLT                                                            1.022476                \n",
       "RBC                                                            0.993603                \n",
       "RDW                                                            1.022395                \n",
       "SBP                                                            1.010808                \n",
       "T3                                                             1.070384                \n",
       "T4                                                             1.008279                \n",
       "TBA                                                            1.066072                \n",
       "TBIL                                                           0.991726                \n",
       "TC                                                             1.027388                \n",
       "TG                                                             1.027639                \n",
       "TPOAb                                                          1.111281                \n",
       "TSH                                                            1.075401                \n",
       "WBC                                                            1.018224                \n",
       "age                                                            1.039424                \n",
       "height                                                         1.000750                \n",
       "weight                                                         1.004826                \n",
       "\n",
       "                      2023Mar~2023Jun vs mean of 2022Mar~2022Jun and 2021Mar~2021Jun  \\\n",
       " waist-circumference                                           0.994662                \n",
       "ADA                                                            1.053452                \n",
       "AFU                                                            1.048839                \n",
       "ALP                                                            0.974872                \n",
       "ALT                                                            1.025062                \n",
       "AST                                                            1.011981                \n",
       "BASO                                                           0.963598                \n",
       "BASO%                                                          0.954259                \n",
       "Cr                                                             1.010697                \n",
       "DBIL                                                           0.975301                \n",
       "DBP                                                            1.016458                \n",
       "EOS                                                            1.034703                \n",
       "EOS%                                                           1.023678                \n",
       "FPG                                                            0.996600                \n",
       "FT4                                                            1.016128                \n",
       "GPDA                                                           0.988741                \n",
       "HCY                                                            1.082360                \n",
       "HDL-C                                                          0.995797                \n",
       "HR                                                             0.999423                \n",
       "Hb                                                             0.990830                \n",
       "HbA1                                                           1.022070                \n",
       "HbA1c                                                          1.024176                \n",
       "Hct                                                            0.997368                \n",
       "IBIL                                                           0.972114                \n",
       "LDL-C                                                          0.999032                \n",
       "LYMPH                                                          1.030862                \n",
       "LYMPH%                                                         1.016692                \n",
       "MCH                                                            0.994454                \n",
       "MCHC                                                           0.993479                \n",
       "MCV                                                            1.001063                \n",
       "MONO                                                           0.998584                \n",
       "MONO%                                                          0.987486                \n",
       "MPV                                                            0.980902                \n",
       "NEUT                                                           1.002433                \n",
       "NEUT%                                                          0.990619                \n",
       "PCT                                                            0.997175                \n",
       "PLT                                                            1.016716                \n",
       "RBC                                                            0.996283                \n",
       "RDW                                                            1.010126                \n",
       "SBP                                                            1.014004                \n",
       "T3                                                             0.998174                \n",
       "T4                                                             1.010895                \n",
       "TBA                                                            1.113135                \n",
       "TBIL                                                           0.973466                \n",
       "TC                                                             1.005610                \n",
       "TG                                                             1.022233                \n",
       "TPOAb                                                          1.087736                \n",
       "TSH                                                            0.970637                \n",
       "WBC                                                            1.012516                \n",
       "age                                                            1.032227                \n",
       "height                                                         1.000251                \n",
       "weight                                                         1.002197                \n",
       "\n",
       "                     variable_p ratio_pre_p ratio_now_p ratio_after_p  \n",
       " waist-circumference        NaN         NaN         NaN           NaN  \n",
       "ADA                         NaN         NaN         NaN           NaN  \n",
       "AFU                         NaN         NaN         NaN           NaN  \n",
       "ALP                         NaN         NaN         NaN           NaN  \n",
       "ALT                         NaN         NaN         NaN           NaN  \n",
       "AST                         NaN         NaN         NaN           NaN  \n",
       "BASO                        NaN         NaN         NaN           NaN  \n",
       "BASO%                       NaN         NaN         NaN           NaN  \n",
       "Cr                          NaN         NaN         NaN           NaN  \n",
       "DBIL                        NaN         NaN         NaN           NaN  \n",
       "DBP                         NaN         NaN         NaN           NaN  \n",
       "EOS                         NaN         NaN         NaN           NaN  \n",
       "EOS%                        NaN         NaN         NaN           NaN  \n",
       "FPG                         NaN         NaN         NaN           NaN  \n",
       "FT4                         NaN         NaN         NaN           NaN  \n",
       "GPDA                        NaN         NaN         NaN           NaN  \n",
       "HCY                         NaN         NaN         NaN           NaN  \n",
       "HDL-C                       NaN         NaN         NaN           NaN  \n",
       "HR                          NaN         NaN         NaN           NaN  \n",
       "Hb                          NaN         NaN         NaN           NaN  \n",
       "HbA1                        NaN         NaN         NaN           NaN  \n",
       "HbA1c                       NaN         NaN         NaN           NaN  \n",
       "Hct                         NaN         NaN         NaN           NaN  \n",
       "IBIL                        NaN         NaN         NaN           NaN  \n",
       "LDL-C                       NaN         NaN         NaN           NaN  \n",
       "LYMPH                       NaN         NaN         NaN           NaN  \n",
       "LYMPH%                      NaN         NaN         NaN           NaN  \n",
       "MCH                         NaN         NaN         NaN           NaN  \n",
       "MCHC                        NaN         NaN         NaN           NaN  \n",
       "MCV                         NaN         NaN         NaN           NaN  \n",
       "MONO                        NaN         NaN         NaN           NaN  \n",
       "MONO%                       NaN         NaN         NaN           NaN  \n",
       "MPV                         NaN         NaN         NaN           NaN  \n",
       "NEUT                        NaN         NaN         NaN           NaN  \n",
       "NEUT%                       NaN         NaN         NaN           NaN  \n",
       "PCT                         NaN         NaN         NaN           NaN  \n",
       "PLT                         NaN         NaN         NaN           NaN  \n",
       "RBC                         NaN         NaN         NaN           NaN  \n",
       "RDW                         NaN         NaN         NaN           NaN  \n",
       "SBP                         NaN         NaN         NaN           NaN  \n",
       "T3                          NaN         NaN         NaN           NaN  \n",
       "T4                          NaN         NaN         NaN           NaN  \n",
       "TBA                         NaN         NaN         NaN           NaN  \n",
       "TBIL                        NaN         NaN         NaN           NaN  \n",
       "TC                          NaN         NaN         NaN           NaN  \n",
       "TG                          NaN         NaN         NaN           NaN  \n",
       "TPOAb                       NaN         NaN         NaN           NaN  \n",
       "TSH                         NaN         NaN         NaN           NaN  \n",
       "WBC                         NaN         NaN         NaN           NaN  \n",
       "age                         NaN         NaN         NaN           NaN  \n",
       "height                      NaN         NaN         NaN           NaN  \n",
       "weight                      NaN         NaN         NaN           NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_ratio_p(my_table):\n",
    "    df_mean = my_table.cont_table[\"P-Value (adjusted)\"]\n",
    "    return df_mean\n",
    "\n",
    "my_table_pre.cont_table[\"P-Value (adjusted)\"]\n",
    "\n",
    "df_res_p = get_ratio_p(my_table_pre).reset_index().drop([\"value\"], axis=1)\n",
    "df_res_p.columns = [\"variable_p\", \"ratio_pre_p\"]\n",
    "df_res_p[\"ratio_now_p\"] = get_ratio_p(my_table_).values\n",
    "df_res_p[\"ratio_after_p\"] = get_ratio_p(my_table_after).values\n",
    "\n",
    "df_res.join(df_res_p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7b9d8263-acc3-4400-a0c7-8a84cd01eb14",
   "metadata": {
    "tags": []
   },
   "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>period</th>\n",
       "      <th>Control-2021</th>\n",
       "      <th>Control-2022</th>\n",
       "      <th>Test-2023</th>\n",
       "      <th>ratio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variable</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BASO%</th>\n",
       "      <td>0.591124</td>\n",
       "      <td>0.569614</td>\n",
       "      <td>0.545007</td>\n",
       "      <td>0.939071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BASO</th>\n",
       "      <td>0.035009</td>\n",
       "      <td>0.034277</td>\n",
       "      <td>0.033140</td>\n",
       "      <td>0.956607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO%</th>\n",
       "      <td>7.063150</td>\n",
       "      <td>6.996380</td>\n",
       "      <td>6.752330</td>\n",
       "      <td>0.960534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MONO</th>\n",
       "      <td>0.421855</td>\n",
       "      <td>0.422647</td>\n",
       "      <td>0.413251</td>\n",
       "      <td>0.978687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cr</th>\n",
       "      <td>67.415287</td>\n",
       "      <td>66.154472</td>\n",
       "      <td>65.373336</td>\n",
       "      <td>0.978864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPV</th>\n",
       "      <td>10.768776</td>\n",
       "      <td>10.720505</td>\n",
       "      <td>10.550380</td>\n",
       "      <td>0.981920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GPDA</th>\n",
       "      <td>75.837276</td>\n",
       "      <td>79.326059</td>\n",
       "      <td>76.389888</td>\n",
       "      <td>0.984638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hb</th>\n",
       "      <td>139.469534</td>\n",
       "      <td>138.700133</td>\n",
       "      <td>137.486243</td>\n",
       "      <td>0.988506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IBIL</th>\n",
       "      <td>7.222855</td>\n",
       "      <td>7.014124</td>\n",
       "      <td>7.037847</td>\n",
       "      <td>0.988671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCHC</th>\n",
       "      <td>331.364588</td>\n",
       "      <td>331.483599</td>\n",
       "      <td>327.711243</td>\n",
       "      <td>0.988797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBIL</th>\n",
       "      <td>11.149700</td>\n",
       "      <td>10.990294</td>\n",
       "      <td>10.978407</td>\n",
       "      <td>0.991726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RBC</th>\n",
       "      <td>4.674519</td>\n",
       "      <td>4.642752</td>\n",
       "      <td>4.628833</td>\n",
       "      <td>0.993603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALP</th>\n",
       "      <td>66.416309</td>\n",
       "      <td>66.137757</td>\n",
       "      <td>65.899068</td>\n",
       "      <td>0.994297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FPG</th>\n",
       "      <td>4.893387</td>\n",
       "      <td>4.885002</td>\n",
       "      <td>4.863884</td>\n",
       "      <td>0.994823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCH</th>\n",
       "      <td>29.896717</td>\n",
       "      <td>29.932410</td>\n",
       "      <td>29.763180</td>\n",
       "      <td>0.994939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>waist-circumference</th>\n",
       "      <td>85.128440</td>\n",
       "      <td>84.589686</td>\n",
       "      <td>84.633484</td>\n",
       "      <td>0.997342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBIL</th>\n",
       "      <td>3.926848</td>\n",
       "      <td>3.975960</td>\n",
       "      <td>3.941531</td>\n",
       "      <td>0.997501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT%</th>\n",
       "      <td>55.210502</td>\n",
       "      <td>53.902298</td>\n",
       "      <td>54.432936</td>\n",
       "      <td>0.997737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hct</th>\n",
       "      <td>42.051345</td>\n",
       "      <td>41.802852</td>\n",
       "      <td>41.922212</td>\n",
       "      <td>0.999883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>height</th>\n",
       "      <td>163.502140</td>\n",
       "      <td>163.695036</td>\n",
       "      <td>163.721300</td>\n",
       "      <td>1.000750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HDL-C</th>\n",
       "      <td>1.418494</td>\n",
       "      <td>1.487641</td>\n",
       "      <td>1.456338</td>\n",
       "      <td>1.002250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCT</th>\n",
       "      <td>0.263481</td>\n",
       "      <td>0.266295</td>\n",
       "      <td>0.265922</td>\n",
       "      <td>1.003904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HR</th>\n",
       "      <td>85.595344</td>\n",
       "      <td>85.226830</td>\n",
       "      <td>85.781448</td>\n",
       "      <td>1.004336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight</th>\n",
       "      <td>59.642522</td>\n",
       "      <td>60.326933</td>\n",
       "      <td>60.274219</td>\n",
       "      <td>1.004826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCV</th>\n",
       "      <td>90.163854</td>\n",
       "      <td>90.243056</td>\n",
       "      <td>90.767293</td>\n",
       "      <td>1.006251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T4</th>\n",
       "      <td>99.374089</td>\n",
       "      <td>98.757786</td>\n",
       "      <td>99.886073</td>\n",
       "      <td>1.008279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH%</th>\n",
       "      <td>35.031208</td>\n",
       "      <td>36.332314</td>\n",
       "      <td>36.014297</td>\n",
       "      <td>1.009320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SBP</th>\n",
       "      <td>120.865379</td>\n",
       "      <td>120.652337</td>\n",
       "      <td>122.064046</td>\n",
       "      <td>1.010808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUT</th>\n",
       "      <td>3.390132</td>\n",
       "      <td>3.336197</td>\n",
       "      <td>3.408091</td>\n",
       "      <td>1.013358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBP</th>\n",
       "      <td>71.568499</td>\n",
       "      <td>71.681448</td>\n",
       "      <td>72.896843</td>\n",
       "      <td>1.017757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WBC</th>\n",
       "      <td>6.046877</td>\n",
       "      <td>6.111916</td>\n",
       "      <td>6.190189</td>\n",
       "      <td>1.018224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1c</th>\n",
       "      <td>5.609701</td>\n",
       "      <td>5.728829</td>\n",
       "      <td>5.772846</td>\n",
       "      <td>1.018271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HbA1</th>\n",
       "      <td>6.808642</td>\n",
       "      <td>6.960203</td>\n",
       "      <td>7.010303</td>\n",
       "      <td>1.018285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RDW</th>\n",
       "      <td>12.647207</td>\n",
       "      <td>12.645656</td>\n",
       "      <td>12.929649</td>\n",
       "      <td>1.022395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLT</th>\n",
       "      <td>246.881311</td>\n",
       "      <td>250.528369</td>\n",
       "      <td>254.294762</td>\n",
       "      <td>1.022476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FT4</th>\n",
       "      <td>13.390386</td>\n",
       "      <td>13.408539</td>\n",
       "      <td>13.758475</td>\n",
       "      <td>1.026793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TC</th>\n",
       "      <td>4.488346</td>\n",
       "      <td>4.720030</td>\n",
       "      <td>4.730287</td>\n",
       "      <td>1.027388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TG</th>\n",
       "      <td>1.137622</td>\n",
       "      <td>1.191828</td>\n",
       "      <td>1.196917</td>\n",
       "      <td>1.027639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LYMPH</th>\n",
       "      <td>2.074739</td>\n",
       "      <td>2.184525</td>\n",
       "      <td>2.196543</td>\n",
       "      <td>1.031419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LDL-C</th>\n",
       "      <td>2.469859</td>\n",
       "      <td>2.575389</td>\n",
       "      <td>2.614102</td>\n",
       "      <td>1.036263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>37.545977</td>\n",
       "      <td>38.545830</td>\n",
       "      <td>39.545830</td>\n",
       "      <td>1.039424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AST</th>\n",
       "      <td>19.344106</td>\n",
       "      <td>20.296319</td>\n",
       "      <td>20.645551</td>\n",
       "      <td>1.041641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADA</th>\n",
       "      <td>8.516909</td>\n",
       "      <td>8.239961</td>\n",
       "      <td>8.766439</td>\n",
       "      <td>1.046310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS%</th>\n",
       "      <td>2.103721</td>\n",
       "      <td>2.199394</td>\n",
       "      <td>2.255429</td>\n",
       "      <td>1.048277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFU</th>\n",
       "      <td>20.339960</td>\n",
       "      <td>20.370175</td>\n",
       "      <td>21.554125</td>\n",
       "      <td>1.058907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TBA</th>\n",
       "      <td>4.889737</td>\n",
       "      <td>5.082927</td>\n",
       "      <td>5.315788</td>\n",
       "      <td>1.066072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T3</th>\n",
       "      <td>1.451517</td>\n",
       "      <td>1.476452</td>\n",
       "      <td>1.567026</td>\n",
       "      <td>1.070384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EOS</th>\n",
       "      <td>0.125789</td>\n",
       "      <td>0.134125</td>\n",
       "      <td>0.139130</td>\n",
       "      <td>1.070589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSH</th>\n",
       "      <td>1.944566</td>\n",
       "      <td>1.876368</td>\n",
       "      <td>2.054518</td>\n",
       "      <td>1.075401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALT</th>\n",
       "      <td>18.118210</td>\n",
       "      <td>19.040811</td>\n",
       "      <td>20.114913</td>\n",
       "      <td>1.082640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TPOAb</th>\n",
       "      <td>41.287368</td>\n",
       "      <td>38.506136</td>\n",
       "      <td>44.336507</td>\n",
       "      <td>1.111281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HCY</th>\n",
       "      <td>8.720972</td>\n",
       "      <td>9.175938</td>\n",
       "      <td>9.968380</td>\n",
       "      <td>1.113978</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "period                Control-2021  Control-2022   Test-2023     ratio\n",
       "variable                                                              \n",
       "BASO%                     0.591124      0.569614    0.545007  0.939071\n",
       "BASO                      0.035009      0.034277    0.033140  0.956607\n",
       "MONO%                     7.063150      6.996380    6.752330  0.960534\n",
       "MONO                      0.421855      0.422647    0.413251  0.978687\n",
       "Cr                       67.415287     66.154472   65.373336  0.978864\n",
       "MPV                      10.768776     10.720505   10.550380  0.981920\n",
       "GPDA                     75.837276     79.326059   76.389888  0.984638\n",
       "Hb                      139.469534    138.700133  137.486243  0.988506\n",
       "IBIL                      7.222855      7.014124    7.037847  0.988671\n",
       "MCHC                    331.364588    331.483599  327.711243  0.988797\n",
       "TBIL                     11.149700     10.990294   10.978407  0.991726\n",
       "RBC                       4.674519      4.642752    4.628833  0.993603\n",
       "ALP                      66.416309     66.137757   65.899068  0.994297\n",
       "FPG                       4.893387      4.885002    4.863884  0.994823\n",
       "MCH                      29.896717     29.932410   29.763180  0.994939\n",
       " waist-circumference     85.128440     84.589686   84.633484  0.997342\n",
       "DBIL                      3.926848      3.975960    3.941531  0.997501\n",
       "NEUT%                    55.210502     53.902298   54.432936  0.997737\n",
       "Hct                      42.051345     41.802852   41.922212  0.999883\n",
       "height                  163.502140    163.695036  163.721300  1.000750\n",
       "HDL-C                     1.418494      1.487641    1.456338  1.002250\n",
       "PCT                       0.263481      0.266295    0.265922  1.003904\n",
       "HR                       85.595344     85.226830   85.781448  1.004336\n",
       "weight                   59.642522     60.326933   60.274219  1.004826\n",
       "MCV                      90.163854     90.243056   90.767293  1.006251\n",
       "T4                       99.374089     98.757786   99.886073  1.008279\n",
       "LYMPH%                   35.031208     36.332314   36.014297  1.009320\n",
       "SBP                     120.865379    120.652337  122.064046  1.010808\n",
       "NEUT                      3.390132      3.336197    3.408091  1.013358\n",
       "DBP                      71.568499     71.681448   72.896843  1.017757\n",
       "WBC                       6.046877      6.111916    6.190189  1.018224\n",
       "HbA1c                     5.609701      5.728829    5.772846  1.018271\n",
       "HbA1                      6.808642      6.960203    7.010303  1.018285\n",
       "RDW                      12.647207     12.645656   12.929649  1.022395\n",
       "PLT                     246.881311    250.528369  254.294762  1.022476\n",
       "FT4                      13.390386     13.408539   13.758475  1.026793\n",
       "TC                        4.488346      4.720030    4.730287  1.027388\n",
       "TG                        1.137622      1.191828    1.196917  1.027639\n",
       "LYMPH                     2.074739      2.184525    2.196543  1.031419\n",
       "LDL-C                     2.469859      2.575389    2.614102  1.036263\n",
       "age                      37.545977     38.545830   39.545830  1.039424\n",
       "AST                      19.344106     20.296319   20.645551  1.041641\n",
       "ADA                       8.516909      8.239961    8.766439  1.046310\n",
       "EOS%                      2.103721      2.199394    2.255429  1.048277\n",
       "AFU                      20.339960     20.370175   21.554125  1.058907\n",
       "TBA                       4.889737      5.082927    5.315788  1.066072\n",
       "T3                        1.451517      1.476452    1.567026  1.070384\n",
       "EOS                       0.125789      0.134125    0.139130  1.070589\n",
       "TSH                       1.944566      1.876368    2.054518  1.075401\n",
       "ALT                      18.118210     19.040811   20.114913  1.082640\n",
       "TPOAb                    41.287368     38.506136   44.336507  1.111281\n",
       "HCY                       8.720972      9.175938    9.968380  1.113978"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_mean = mytable.cont_describe[\"mean\"]\n",
    "df_mean[\"ratio\"] = df_mean.apply(lambda x: 2*x[\"Test-2023\"] / (x[\"Control-2021\"]+x[\"Control-2022\"]), axis=1)\n",
    "df_mean.sort_values([\"ratio\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d2c5888-22df-42a3-9504-9906aec27973",
   "metadata": {},
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   "source": []
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "8f9ce2d1-cc51-4d66-a618-96b98ae32702",
   "metadata": {},
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   "source": []
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