{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "775553f7",
   "metadata": {},
   "source": [
    "# 1：目标公司与同业公司基本信息整理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f293e5d",
   "metadata": {},
   "source": [
    "我们选择的目标公司是春风动力，同业公司为宗申动力、钱江摩托、信隆健康、千里科技、隆鑫通用、新日股份、爱玛科技、九号公司、涛涛车业、绿通科技和华洋赛车。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0e8bd21b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T00:25:57.487503Z",
     "start_time": "2026-05-28T00:25:56.974298Z"
    }
   },
   "outputs": [],
   "source": [
    "#导入需要用到的库\n",
    "import tushare as ts\n",
    "import pandas as pd\n",
    "import time\n",
    "\n",
    "TOKEN = 'd03626ff9727d599aa92579545fbdd63e321786263aeddce433b553b'\n",
    "pro = ts.pro_api(TOKEN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3229523c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T00:25:59.158215Z",
     "start_time": "2026-05-28T00:25:58.556103Z"
    }
   },
   "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>股票代码</th>\n",
       "      <th>公司全称</th>\n",
       "      <th>法人代表</th>\n",
       "      <th>总经理</th>\n",
       "      <th>注册资本(万元)</th>\n",
       "      <th>员工人数</th>\n",
       "      <th>所在省份</th>\n",
       "      <th>所在城市</th>\n",
       "      <th>注册日期</th>\n",
       "      <th>主要业务</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>603129.SH</td>\n",
       "      <td>浙江春风动力股份有限公司</td>\n",
       "      <td>赖民杰</td>\n",
       "      <td>赖民杰</td>\n",
       "      <td>15348.2763</td>\n",
       "      <td>6911</td>\n",
       "      <td>浙江</td>\n",
       "      <td>杭州市</td>\n",
       "      <td>20031209</td>\n",
       "      <td>主营业务为全地形车,摩托车,游艇及休闲运动装备等后市场用品的研发,生产和销售.公司产品包括4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000913.SZ</td>\n",
       "      <td>浙江钱江摩托股份有限公司</td>\n",
       "      <td>徐志豪</td>\n",
       "      <td>郭东劭</td>\n",
       "      <td>52641.1000</td>\n",
       "      <td>5602</td>\n",
       "      <td>浙江</td>\n",
       "      <td>台州市</td>\n",
       "      <td>19990328</td>\n",
       "      <td>主要产品:摩托车整车,摩托车配件及加工.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>001696.SZ</td>\n",
       "      <td>重庆宗申动力机械股份有限公司</td>\n",
       "      <td>黄培国</td>\n",
       "      <td>黄培国</td>\n",
       "      <td>114502.6920</td>\n",
       "      <td>9459</td>\n",
       "      <td>重庆</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>19890314</td>\n",
       "      <td>主要产品:摩托车发动机及零配件.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>002105.SZ</td>\n",
       "      <td>深圳信隆健康产业发展股份有限公司</td>\n",
       "      <td>廖学金</td>\n",
       "      <td>廖学湖</td>\n",
       "      <td>36624.1950</td>\n",
       "      <td>2477</td>\n",
       "      <td>广东</td>\n",
       "      <td>深圳市</td>\n",
       "      <td>19911028</td>\n",
       "      <td>主要产品:自行车零配件和运动健身康复器材产品.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>301322.SZ</td>\n",
       "      <td>广东绿通新能源电动车科技股份有限公司</td>\n",
       "      <td>张志江</td>\n",
       "      <td>张志江</td>\n",
       "      <td>14128.7878</td>\n",
       "      <td>663</td>\n",
       "      <td>广东</td>\n",
       "      <td>东莞市</td>\n",
       "      <td>20040511</td>\n",
       "      <td>公司是一家从事场地电动车研发,生产和销售的高新技术企业.公司主要产品为场地电动车系列产品,根...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>301345.SZ</td>\n",
       "      <td>浙江涛涛车业股份有限公司</td>\n",
       "      <td>曹马涛</td>\n",
       "      <td>曹马涛</td>\n",
       "      <td>10904.9071</td>\n",
       "      <td>3013</td>\n",
       "      <td>浙江</td>\n",
       "      <td>丽水市</td>\n",
       "      <td>20150924</td>\n",
       "      <td>专注于户外休闲娱乐兼具短途交通代步功能的汽动车,电动车及其配件,用品研发,生产和销售,汽动车...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>601777.SH</td>\n",
       "      <td>重庆千里科技股份有限公司</td>\n",
       "      <td>印奇</td>\n",
       "      <td>周宗成</td>\n",
       "      <td>452110.0071</td>\n",
       "      <td>6949</td>\n",
       "      <td>重庆</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>19971201</td>\n",
       "      <td>主要产品:摩托车,摩托车发动机,乘用车,乘用车发动机,通用汽油机及终端产品(发电机组,水泵,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>603529.SH</td>\n",
       "      <td>爱玛科技集团股份有限公司</td>\n",
       "      <td>张剑</td>\n",
       "      <td>张剑</td>\n",
       "      <td>86789.2982</td>\n",
       "      <td>9134</td>\n",
       "      <td>天津</td>\n",
       "      <td>天津市</td>\n",
       "      <td>19990927</td>\n",
       "      <td>主营业务:电动自行车的研发,生产及销售.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>603766.SH</td>\n",
       "      <td>隆鑫通用动力股份有限公司</td>\n",
       "      <td>李耀</td>\n",
       "      <td>龚晖</td>\n",
       "      <td>205354.1850</td>\n",
       "      <td>10529</td>\n",
       "      <td>重庆</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>20070608</td>\n",
       "      <td>主要产品包括:摩托车及配件,发动机及配件,农业机械装备及配件和发电机组等.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>603787.SH</td>\n",
       "      <td>江苏新日电动车股份有限公司</td>\n",
       "      <td>张崇舜</td>\n",
       "      <td>赵学忠</td>\n",
       "      <td>23014.3790</td>\n",
       "      <td>2251</td>\n",
       "      <td>江苏</td>\n",
       "      <td>无锡市</td>\n",
       "      <td>20070716</td>\n",
       "      <td>公司主营业务为电动自行车的研发,生产与销售.公司的主导产品为简易款电动自行车,豪华款电动自行...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>920058.BJ</td>\n",
       "      <td>浙江华洋赛车股份有限公司</td>\n",
       "      <td>戴鹏</td>\n",
       "      <td>戴鹏</td>\n",
       "      <td>5605.6110</td>\n",
       "      <td>718</td>\n",
       "      <td>浙江</td>\n",
       "      <td>丽水市</td>\n",
       "      <td>20040310</td>\n",
       "      <td>两轮越野摩托车和全地形车.公司专业从事非道路越野车的自主研发,生产和销售.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>689009.SH</td>\n",
       "      <td>九号有限公司</td>\n",
       "      <td>高禄峰</td>\n",
       "      <td>陈中元</td>\n",
       "      <td>507500.0000</td>\n",
       "      <td>6995</td>\n",
       "      <td>None</td>\n",
       "      <td>GrandCayman</td>\n",
       "      <td>20141210</td>\n",
       "      <td>主营业务为各类智能短程移动设备的设计,研发,生产,销售及服务.公司主要产品分为智能电动平衡车...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         股票代码                公司全称 法人代表  总经理     注册资本(万元)   员工人数  所在省份  \\\n",
       "0   603129.SH        浙江春风动力股份有限公司  赖民杰  赖民杰   15348.2763   6911    浙江   \n",
       "1   000913.SZ        浙江钱江摩托股份有限公司  徐志豪  郭东劭   52641.1000   5602    浙江   \n",
       "2   001696.SZ      重庆宗申动力机械股份有限公司  黄培国  黄培国  114502.6920   9459    重庆   \n",
       "3   002105.SZ    深圳信隆健康产业发展股份有限公司  廖学金  廖学湖   36624.1950   2477    广东   \n",
       "4   301322.SZ  广东绿通新能源电动车科技股份有限公司  张志江  张志江   14128.7878    663    广东   \n",
       "5   301345.SZ        浙江涛涛车业股份有限公司  曹马涛  曹马涛   10904.9071   3013    浙江   \n",
       "6   601777.SH        重庆千里科技股份有限公司   印奇  周宗成  452110.0071   6949    重庆   \n",
       "7   603529.SH        爱玛科技集团股份有限公司   张剑   张剑   86789.2982   9134    天津   \n",
       "8   603766.SH        隆鑫通用动力股份有限公司   李耀   龚晖  205354.1850  10529    重庆   \n",
       "9   603787.SH       江苏新日电动车股份有限公司  张崇舜  赵学忠   23014.3790   2251    江苏   \n",
       "10  920058.BJ        浙江华洋赛车股份有限公司   戴鹏   戴鹏    5605.6110    718    浙江   \n",
       "11  689009.SH              九号有限公司  高禄峰  陈中元  507500.0000   6995  None   \n",
       "\n",
       "           所在城市      注册日期                                               主要业务  \n",
       "0           杭州市  20031209  主营业务为全地形车,摩托车,游艇及休闲运动装备等后市场用品的研发,生产和销售.公司产品包括4...  \n",
       "1           台州市  19990328                               主要产品:摩托车整车,摩托车配件及加工.  \n",
       "2           重庆市  19890314                                   主要产品:摩托车发动机及零配件.  \n",
       "3           深圳市  19911028                            主要产品:自行车零配件和运动健身康复器材产品.  \n",
       "4           东莞市  20040511  公司是一家从事场地电动车研发,生产和销售的高新技术企业.公司主要产品为场地电动车系列产品,根...  \n",
       "5           丽水市  20150924  专注于户外休闲娱乐兼具短途交通代步功能的汽动车,电动车及其配件,用品研发,生产和销售,汽动车...  \n",
       "6           重庆市  19971201  主要产品:摩托车,摩托车发动机,乘用车,乘用车发动机,通用汽油机及终端产品(发电机组,水泵,...  \n",
       "7           天津市  19990927                               主营业务:电动自行车的研发,生产及销售.  \n",
       "8           重庆市  20070608              主要产品包括:摩托车及配件,发动机及配件,农业机械装备及配件和发电机组等.  \n",
       "9           无锡市  20070716  公司主营业务为电动自行车的研发,生产与销售.公司的主导产品为简易款电动自行车,豪华款电动自行...  \n",
       "10          丽水市  20040310              两轮越野摩托车和全地形车.公司专业从事非道路越野车的自主研发,生产和销售.  \n",
       "11  GrandCayman  20141210  主营业务为各类智能短程移动设备的设计,研发,生产,销售及服务.公司主要产品分为智能电动平衡车...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#获取公司基本信息表\n",
    "\n",
    "# 获取目标公司春风动力的基本信息\n",
    "target_df = pro.stock_company(\n",
    "    ts_code='603129.SH',\n",
    "    fields='ts_code,com_name,chairman,manager,reg_capital,employees,province,city,setup_date,main_business'\n",
    ")\n",
    "\n",
    "# 获取同业公司的基本信息\n",
    "peer_df = pro.stock_company(\n",
    "    ts_code='001696.SZ,000913.SZ,002105.SZ,601777.SH,603766.SH,603787.SH,603529.SH,301345.SZ,301322.SZ,920058.BJ',\n",
    "    fields='ts_code,com_name,chairman,manager,reg_capital,employees,province,city,setup_date,main_business'\n",
    ")\n",
    "\n",
    "# 在获取九号公司数据时，我们发现它的注册资本是以亿美元为单位的，所以我们需要单独获取并进行处理\n",
    "jiuhao_df = pro.stock_company(\n",
    "    ts_code='689009.SH',\n",
    "    fields='ts_code,com_name,chairman,manager,employees,province,city,setup_date,main_business'\n",
    ")\n",
    "\n",
    "USD_TO_CNY = 7.25   # 用最新汇率来换算九号公司的注册资本\n",
    "jiuhao_df['reg_capital'] = 7 * 10000 * USD_TO_CNY\n",
    "\n",
    "#  合并所有数据\n",
    "company_df = pd.concat([target_df, peer_df, jiuhao_df], ignore_index=True)\n",
    "\n",
    "# 把字段显示为中文\n",
    "company_df = company_df.rename(columns={\n",
    "    'ts_code': '股票代码',\n",
    "    'com_name': '公司全称',\n",
    "    'chairman': '法人代表',\n",
    "    'manager': '总经理',\n",
    "    'reg_capital': '注册资本(万元)',\n",
    "    'employees': '员工人数',\n",
    "    'province': '所在省份',\n",
    "    'city': '所在城市',\n",
    "    'setup_date': '注册日期',\n",
    "    'main_business': '主要业务'\n",
    "})\n",
    "\n",
    "company_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cee72d2",
   "metadata": {},
   "source": [
    "# 2.财务指标数据获取与清洗"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "01dcc4b9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T00:26:37.015545Z",
     "start_time": "2026-05-28T00:26:01.730289Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import tushare as ts\n",
    "pro = ts.pro_api('6e8875b56c393fd3b417f1defc0d133184c97ba147c49780309e314b')\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# 定义获取报表函数\n",
    "def access_data(comps,codes,years):\n",
    "    def rename_col(data):\n",
    "        rename_sheet = pd.read_excel('重命名.xlsx')\n",
    "        eng = rename_sheet['名称'].tolist()\n",
    "        chi = rename_sheet['描述'].tolist()\n",
    "        re_dict = dict(zip(eng,chi))\n",
    "        data = data.rename(columns = re_dict)\n",
    "        return data\n",
    "    for i in range(len(comps)):\n",
    "        # 各新建一个空DataFrame\n",
    "        df_balance = pd.DataFrame()\n",
    "        df_income = pd.DataFrame()\n",
    "        df_cash = pd.DataFrame()\n",
    "        for year in years:\n",
    "            df_balance0 = pro.balancesheet(ts_code=codes[i],period=str(year)+'1231')[-1:] # 每年获取到的报表可能有2份，一份是会计调整前，一份是会计调整后的，我们只需要调整后的报表，因此在每张获取的报表中我们选择最后一张表即可\n",
    "            df_income0 = pro.income(ts_code=codes[i],period=str(year)+'1231')[-1:]\n",
    "            df_cash0 = pro.cashflow(ts_code=codes[i],period=str(year)+'1231')[-1:]\n",
    "            # 拼接各年份报表\n",
    "            df_balance = pd.concat([df_balance,df_balance0])\n",
    "            df_income = pd.concat([df_income,df_income0])\n",
    "            df_cash = pd.concat([df_cash,df_cash0])\n",
    "        # 更改索引名称\n",
    "        df_balance = rename_col(df_balance)\n",
    "        df_income = rename_col(df_income)\n",
    "        df_cash = rename_col(df_cash)\n",
    "        # 再次去重\n",
    "        df_balance = df_balance.drop_duplicates(subset=['报告期'])\n",
    "        df_income = df_income.drop_duplicates(subset=['报告期'])\n",
    "        df_cash = df_cash.drop_duplicates(subset=['报告期'])\n",
    "        # 按日期升序排序\n",
    "        df_balance = df_balance.sort_values('报告期', ascending=True)\n",
    "        df_income = df_income.sort_values('报告期', ascending=True)\n",
    "        df_cash = df_cash.sort_values('报告期', ascending=True)\n",
    "        \n",
    "        # 保存为表格\n",
    "        if '*' in comps[i]:  # 防止公司名称里有*，例如2022年的*ST皇台，*ST表示有退市风险，但是文件名不可以有*号，所以做替换处理，这个之后的章节会用到\n",
    "            comps[i] = comps[i].replace('*','')\n",
    "#         writer = pd.ExcelWriter(comps[i]+'.xlsx')  # 这个是向同一个Excel文件写入多张表的技巧\n",
    "        xlsxname =comps[i]+'.xlsx'\n",
    "        writer = pd.ExcelWriter(comps[i]+'.xlsx', engine='openpyxl')\n",
    "        df_balance.to_excel(writer, sheet_name='资产负债表', index=False)\n",
    "        df_income.to_excel(writer, sheet_name='利润表', index=False)\n",
    "        df_cash.to_excel(writer, sheet_name='现金流量表', index=False)\n",
    "        writer.close()\n",
    "        \n",
    "\n",
    "# 获取摩托车行业的具体股票代码和名称，用于后续爬取报表数据\n",
    "stock_basic = pro.stock_basic(exchange='',list_status='L')\n",
    "mtc_com = stock_basic[stock_basic['industry'] == '摩托车'].copy()\n",
    "mtc_com = mtc_com.sort_values('ts_code').reset_index(drop=True)\n",
    "mtc_code = mtc_com['ts_code'].tolist()\n",
    "mtc_name = mtc_com['name'].tolist()\n",
    "mtc_com = mtc_com.rename(columns={'ts_code':'TS股票代码','name':'名称'}) # 改成中文，便于后续数据合并\n",
    "\n",
    "years = [2025,2024,2023,2022,2021,2020]\n",
    "\n",
    "\n",
    "# 调用定义的函数，爬取摩托车行业中每个公司的报表\n",
    "access_data(mtc_name,mtc_code,years)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c1d2363",
   "metadata": {},
   "source": [
    "# 3.目标公司财务静态分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ce6f0f76",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T00:27:30.261057Z",
     "start_time": "2026-05-28T00:27:28.116796Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# 定义财务比率表生成函数\n",
    "def ratio_sheet(comp):\n",
    "    # 读取报表数据\n",
    "    df_balancesheet = pd.read_excel(comp + '.xlsx', sheet_name='资产负债表')\n",
    "    df_income = pd.read_excel(comp + '.xlsx', sheet_name= '利润表')\n",
    "    df_cashflow = pd.read_excel(comp + '.xlsx', sheet_name='现金流量表')\n",
    "    # 报表拼接\n",
    "    data = pd.merge(df_income,df_balancesheet,on = ['报告期','TS股票代码','公告日期','实际公告日期','报表类型','公司类型'])\n",
    "    data = pd.merge(data,df_cashflow,on = ['报告期','TS股票代码','公告日期','实际公告日期','报表类型','公司类型'])\n",
    "    # 把空值填充为0，防止计算出错\n",
    "    data = data.fillna(0)\n",
    "    # 把相关数据的上期余额加入新表，包括股东权益、存货、资产总计、应收账款、营业收入、营业利润、负债合计、净利润(不含少数股东损益)\n",
    "    columns0 = ['股东权益合计(不含少数股东权益)', '存货', '资产总计', '应收账款', '营业收入', '营业利润', '负债合计', '净利润(不含少数股东损益)']\n",
    "    for column in columns0:\n",
    "        data[column+'(上期)'] = data[column].shift(1)\n",
    "    # 不要最后一行数据了（因为它没有上期数据）\n",
    "    data = data[1:]\n",
    "    #df.shape 返回元组（行，列）\n",
    "    # 计算各项指标\n",
    "    # 盈利能力\n",
    "    data['毛利率'] = round((data['营业收入']-data['减:营业成本'])/data['营业收入'],4) \n",
    "    data['营业利润率'] = round((data['营业利润'])/data['营业收入'],4) \n",
    "    data['净利润率'] = round(data['净利润(含少数股东损益)']/data['营业收入'],4) \n",
    "    data['ROE'] = round(data['净利润(不含少数股东损益)']/((data['股东权益合计(不含少数股东权益)']+data['股东权益合计(不含少数股东权益)(上期)'])/2),4)\n",
    "    # 营运能力\n",
    "    data['存货周转率'] = round(data['减:营业成本']/((data['存货']+data['存货(上期)'])/2),4)\n",
    "    data['总资产周转率'] = round(data['营业收入']/((data['资产总计']+data['资产总计(上期)'])/2),4)\n",
    "    data['应收账款周转率'] = round(data['营业收入']/((data['应收账款']+data['应收账款(上期)'])/2),4)\n",
    "    # 偿债能力\n",
    "    data['流动比率'] = round(data['流动资产合计']/data['流动负债合计'],4) \n",
    "    data['速动比率'] = round((data['流动资产合计']-data['存货']-data['预付款项'])/data['流动负债合计'],4)\n",
    "    data['资产负债率'] = round(data['负债合计']/data['资产总计'],4) \n",
    "    # 成长能力\n",
    "    data['营业收入增长率'] = round((data['营业收入']-data['营业收入(上期)'])/data['营业收入(上期)'],4)\n",
    "    data['营业利润增长率'] = round((data['营业利润']-data['营业利润(上期)'])/data['营业利润(上期)'],4)\n",
    "    data['净利润增长率'] = round((data['净利润(不含少数股东损益)'] - data['净利润(不含少数股东损益)(上期)']) / data['净利润(不含少数股东损益)(上期)'], 4)\n",
    "    # 取出财务比率\n",
    "    \n",
    "    df_ratio = data[['报告期','毛利率','营业利润率','净利润率','ROE','存货周转率','总资产周转率','应收账款周转率','流动比率','速动比率','资产负债率','营业收入增长率','营业利润增长率','净利润增长率']]\n",
    "    df_ratio = df_ratio.T # 转置\n",
    "\n",
    "    # 因为上一行代码转置之后，第一行是0/1/2/3……，我们希望把第二行的报告期作为表头，并从第二行开始取数\n",
    "    df_ratio.columns = df_ratio.iloc[0].apply(lambda x:int(int(x)/10000))  # 重新命名表头，并且通过apply+lambda配合int取整函数将日期变成整数格式（原本保存成了小数格式）\n",
    "    df_ratio = df_ratio[1:]\n",
    "    \n",
    "    # 把财务比率保存为现有表格中的sheet\n",
    "    if '*' in comp:  \n",
    "    # 防止公司名称里有*，例如2022年的*ST皇台，*ST表示有退市风险，\n",
    "        comp = comp.replace('*','')\n",
    "    writer = pd.ExcelWriter(comp+'.xlsx',mode=\"a\", engine=\"openpyxl\")\n",
    "    df_ratio.to_excel(writer,'财务比率表')\n",
    "    writer.close()\n",
    "\n",
    "# 调用定义的函数，爬取摩托车行业中每个公司的财务比率表\n",
    "for comp in mtc_name:\n",
    "    ratio_sheet(comp)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d174591",
   "metadata": {},
   "source": [
    "# 4.目标公司财务趋势分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fe7fb7eb",
   "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>指标</th>\n",
       "      <th>ROE</th>\n",
       "      <th>毛利率</th>\n",
       "      <th>净利润率</th>\n",
       "      <th>营业收入增长率</th>\n",
       "      <th>净利润增长率</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年份</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>2021</th>\n",
       "      <td>16.04</td>\n",
       "      <td>21.53</td>\n",
       "      <td>5.23</td>\n",
       "      <td>73.71</td>\n",
       "      <td>12.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>17.87</td>\n",
       "      <td>25.37</td>\n",
       "      <td>6.50</td>\n",
       "      <td>44.73</td>\n",
       "      <td>70.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>21.78</td>\n",
       "      <td>33.50</td>\n",
       "      <td>8.73</td>\n",
       "      <td>6.44</td>\n",
       "      <td>43.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>26.20</td>\n",
       "      <td>30.06</td>\n",
       "      <td>9.93</td>\n",
       "      <td>24.18</td>\n",
       "      <td>46.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2025</th>\n",
       "      <td>24.46</td>\n",
       "      <td>26.94</td>\n",
       "      <td>8.78</td>\n",
       "      <td>31.30</td>\n",
       "      <td>13.83</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "指标      ROE    毛利率  净利润率  营业收入增长率  净利润增长率\n",
       "年份                                       \n",
       "2021  16.04  21.53  5.23    73.71   12.78\n",
       "2022  17.87  25.37  6.50    44.73   70.43\n",
       "2023  21.78  33.50  8.73     6.44   43.65\n",
       "2024  26.20  30.06  9.93    24.18   46.08\n",
       "2025  24.46  26.94  8.78    31.30   13.83"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "target_company = '春风动力'\n",
    "trend_indicators = ['ROE', '毛利率', '净利润率', '营业收入增长率', '净利润增长率']\n",
    "\n",
    "def load_ratio_table(company):\n",
    "    ratio = pd.read_excel(f'{company}.xlsx', sheet_name='财务比率表')\n",
    "    ratio = ratio.rename(columns={ratio.columns[0]: '指标'}).set_index('指标')\n",
    "    year_columns = {}\n",
    "    for column in ratio.columns:\n",
    "        year_text = ''.join([char for char in str(column) if char.isdigit()])\n",
    "        if len(year_text) >= 4:\n",
    "            year_columns[column] = int(year_text[:4])\n",
    "    ratio = ratio[list(year_columns.keys())].rename(columns=year_columns)\n",
    "    ratio = ratio.apply(pd.to_numeric, errors='coerce').replace([np.inf, -np.inf], np.nan)\n",
    "    ratio = ratio.sort_index(axis=1)\n",
    "    return ratio\n",
    "\n",
    "def judge_trend(series, threshold=0.01):\n",
    "    valid_series = series.dropna()\n",
    "    if len(valid_series) < 2:\n",
    "        return '数据不足'\n",
    "    x = np.arange(len(valid_series))\n",
    "    slope = np.polyfit(x, valid_series.values, 1)[0]\n",
    "    change = valid_series.iloc[-1] - valid_series.iloc[0]\n",
    "    volatility = valid_series.std()\n",
    "    if change > threshold and slope > 0:\n",
    "        return '改善'\n",
    "    if change < -threshold and slope < 0:\n",
    "        return '恶化'\n",
    "    if volatility > threshold * 2:\n",
    "        return '波动'\n",
    "    return '基本稳定'\n",
    "\n",
    "target_ratio = load_ratio_table(target_company)\n",
    "target_trend = target_ratio.reindex(trend_indicators).T\n",
    "target_trend.index.name = '年份'\n",
    "target_trend_percent = (target_trend * 100).round(2)\n",
    "target_trend_percent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "85404202",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 5))\n",
    "plt.plot(target_trend.index, target_trend['ROE'] * 100, marker='o', linewidth=2.5, color='#1f77b4')\n",
    "plt.title('春风动力ROE趋势图', fontsize=15)\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('ROE(%)')\n",
    "plt.xticks(target_trend.index)\n",
    "plt.grid(alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(9, 5))\n",
    "plt.plot(target_trend.index, target_trend['毛利率'] * 100, marker='o', linewidth=2.5, label='毛利率')\n",
    "plt.plot(target_trend.index, target_trend['净利润率'] * 100, marker='s', linewidth=2.5, label='净利润率')\n",
    "plt.title('春风动力毛利率与净利润率趋势图', fontsize=15)\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('比率(%)')\n",
    "plt.xticks(target_trend.index)\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f0572bd5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 5))\n",
    "plt.plot(target_trend.index, target_trend['营业收入增长率'] * 100, marker='o', linewidth=2.5, label='营业收入增长率')\n",
    "plt.plot(target_trend.index, target_trend['净利润增长率'] * 100, marker='s', linewidth=2.5, label='净利润增长率')\n",
    "plt.axhline(0, color='gray', linewidth=1)\n",
    "plt.title('春风动力营业收入与净利润增长率趋势图', fontsize=15)\n",
    "plt.xlabel('年份')\n",
    "plt.ylabel('增长率(%)')\n",
    "plt.xticks(target_trend.index)\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "e60c5b5e",
   "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>指标</th>\n",
       "      <th>期初值(%)</th>\n",
       "      <th>期末值(%)</th>\n",
       "      <th>变化(百分点)</th>\n",
       "      <th>趋势判断</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ROE</td>\n",
       "      <td>16.04</td>\n",
       "      <td>24.46</td>\n",
       "      <td>8.42</td>\n",
       "      <td>改善</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>毛利率</td>\n",
       "      <td>21.53</td>\n",
       "      <td>26.94</td>\n",
       "      <td>5.41</td>\n",
       "      <td>改善</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>净利润率</td>\n",
       "      <td>5.23</td>\n",
       "      <td>8.78</td>\n",
       "      <td>3.55</td>\n",
       "      <td>改善</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>营业收入增长率</td>\n",
       "      <td>73.71</td>\n",
       "      <td>31.30</td>\n",
       "      <td>-42.41</td>\n",
       "      <td>恶化</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>净利润增长率</td>\n",
       "      <td>12.78</td>\n",
       "      <td>13.83</td>\n",
       "      <td>1.05</td>\n",
       "      <td>波动</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        指标  期初值(%)  期末值(%)  变化(百分点) 趋势判断\n",
       "0      ROE   16.04   24.46     8.42   改善\n",
       "1      毛利率   21.53   26.94     5.41   改善\n",
       "2     净利润率    5.23    8.78     3.55   改善\n",
       "3  营业收入增长率   73.71   31.30   -42.41   恶化\n",
       "4   净利润增长率   12.78   13.83     1.05   波动"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trend_judgement = pd.DataFrame({\n",
    "    '指标': trend_indicators,\n",
    "    '期初值(%)': [round(target_trend[indicator].dropna().iloc[0] * 100, 2) if target_trend[indicator].dropna().size > 0 else np.nan for indicator in trend_indicators],\n",
    "    '期末值(%)': [round(target_trend[indicator].dropna().iloc[-1] * 100, 2) if target_trend[indicator].dropna().size > 0 else np.nan for indicator in trend_indicators],\n",
    "    '变化(百分点)': [round((target_trend[indicator].dropna().iloc[-1] - target_trend[indicator].dropna().iloc[0]) * 100, 2) if target_trend[indicator].dropna().size > 1 else np.nan for indicator in trend_indicators],\n",
    "    '趋势判断': [judge_trend(target_trend[indicator]) for indicator in trend_indicators]\n",
    "})\n",
    "trend_judgement"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "382b8007",
   "metadata": {},
   "source": [
    "### 财务趋势分析结论\n",
    "\n",
    "根据 2021—2025 年财务趋势数据，春风动力整体呈改善趋势。ROE 从 16.04% 提高至 24.46%，毛利率从 21.53% 提高至 26.94%，净利润率从 5.23% 提高至 8.78%，说明公司盈利能力整体增强。\n",
    "\n",
    "从成长性来看，营业收入增长率由 73.71% 回落至 31.30%，反映公司在高速增长后收入增速有所放缓；净利润增长率由 12.78% 小幅提高至 13.83%，但期间波动较明显。综合 5 项核心指标看，其中 3 项改善、1 项恶化、1 项波动，说明春风动力盈利质量改善较明显，但收入增速回落和利润增长稳定性仍需持续关注。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84aa036e",
   "metadata": {},
   "source": [
    "# 5.同业比较分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8f3e6cc1",
   "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>指标</th>\n",
       "      <th>ROE</th>\n",
       "      <th>毛利率</th>\n",
       "      <th>净利润率</th>\n",
       "      <th>营业收入增长率</th>\n",
       "      <th>净利润增长率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>钱江摩托</th>\n",
       "      <td>13.35</td>\n",
       "      <td>26.46</td>\n",
       "      <td>10.09</td>\n",
       "      <td>9.74</td>\n",
       "      <td>35.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宗申动力</th>\n",
       "      <td>9.73</td>\n",
       "      <td>13.17</td>\n",
       "      <td>5.13</td>\n",
       "      <td>11.16</td>\n",
       "      <td>5.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信隆健康</th>\n",
       "      <td>9.92</td>\n",
       "      <td>18.44</td>\n",
       "      <td>3.44</td>\n",
       "      <td>-2.71</td>\n",
       "      <td>-0.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绿通科技</th>\n",
       "      <td>23.33</td>\n",
       "      <td>28.11</td>\n",
       "      <td>16.26</td>\n",
       "      <td>19.28</td>\n",
       "      <td>31.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>涛涛车业</th>\n",
       "      <td>23.20</td>\n",
       "      <td>36.56</td>\n",
       "      <td>14.40</td>\n",
       "      <td>25.16</td>\n",
       "      <td>35.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>千里科技</th>\n",
       "      <td>0.70</td>\n",
       "      <td>10.00</td>\n",
       "      <td>-1.57</td>\n",
       "      <td>30.24</td>\n",
       "      <td>53.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>春风动力</th>\n",
       "      <td>21.27</td>\n",
       "      <td>27.48</td>\n",
       "      <td>7.83</td>\n",
       "      <td>36.07</td>\n",
       "      <td>37.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱玛科技</th>\n",
       "      <td>24.14</td>\n",
       "      <td>16.14</td>\n",
       "      <td>7.98</td>\n",
       "      <td>14.88</td>\n",
       "      <td>40.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>隆鑫通用</th>\n",
       "      <td>9.98</td>\n",
       "      <td>17.26</td>\n",
       "      <td>5.04</td>\n",
       "      <td>13.59</td>\n",
       "      <td>33.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新日股份</th>\n",
       "      <td>5.53</td>\n",
       "      <td>13.99</td>\n",
       "      <td>1.53</td>\n",
       "      <td>-2.92</td>\n",
       "      <td>243.65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>九号公司-WD</th>\n",
       "      <td>15.35</td>\n",
       "      <td>26.79</td>\n",
       "      <td>6.13</td>\n",
       "      <td>30.56</td>\n",
       "      <td>128.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华洋赛车</th>\n",
       "      <td>41.38</td>\n",
       "      <td>21.21</td>\n",
       "      <td>11.22</td>\n",
       "      <td>30.80</td>\n",
       "      <td>35.81</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "指标         ROE    毛利率   净利润率  营业收入增长率  净利润增长率\n",
       "钱江摩托     13.35  26.46  10.09     9.74   35.26\n",
       "宗申动力      9.73  13.17   5.13    11.16    5.48\n",
       "信隆健康      9.92  18.44   3.44    -2.71   -0.55\n",
       "绿通科技     23.33  28.11  16.26    19.28   31.71\n",
       "涛涛车业     23.20  36.56  14.40    25.16   35.08\n",
       "千里科技      0.70  10.00  -1.57    30.24   53.13\n",
       "春风动力     21.27  27.48   7.83    36.07   37.35\n",
       "爱玛科技     24.14  16.14   7.98    14.88   40.30\n",
       "隆鑫通用      9.98  17.26   5.04    13.59   33.40\n",
       "新日股份      5.53  13.99   1.53    -2.92  243.65\n",
       "九号公司-WD  15.35  26.79   6.13    30.56  128.95\n",
       "华洋赛车     41.38  21.21  11.22    30.80   35.81"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "peer_companies = mtc_name\n",
    "peer_indicators = ['ROE', '毛利率', '净利润率', '营业收入增长率', '净利润增长率']\n",
    "\n",
    "peer_ratio_list = []\n",
    "for company in peer_companies:\n",
    "    ratio = load_ratio_table(company)\n",
    "    indicator_mean = ratio.reindex(peer_indicators).T.mean(skipna=True)\n",
    "    indicator_mean.name = company\n",
    "    peer_ratio_list.append(indicator_mean)\n",
    "\n",
    "peer_compare = pd.concat(peer_ratio_list, axis=1).T\n",
    "peer_compare_percent = (peer_compare * 100).round(2)\n",
    "peer_compare_percent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "21b12aab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "x = np.arange(len(peer_companies))\n",
    "bar_width = 0.35\n",
    "plt.bar(x - bar_width / 2, peer_compare['ROE'] * 100, width=bar_width, label='ROE', color='#4C78A8')\n",
    "plt.bar(x + bar_width / 2, peer_compare['毛利率'] * 100, width=bar_width, label='毛利率', color='#F58518')\n",
    "plt.title('同业公司ROE与毛利率对比图', fontsize=15)\n",
    "plt.xlabel('公司')\n",
    "plt.ylabel('比率(%)')\n",
    "plt.xticks(x, peer_companies, rotation=0, ha='center')\n",
    "plt.legend()\n",
    "plt.grid(axis='y', alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6edbd8c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "x = np.arange(len(peer_companies))\n",
    "bar_width = 0.35\n",
    "plt.bar(x - bar_width / 2, peer_compare['营业收入增长率'] * 100, width=bar_width, label='营业收入增长率', color='#54A24B')\n",
    "plt.bar(x + bar_width / 2, peer_compare['净利润增长率'] * 100, width=bar_width, label='净利润增长率', color='#E45756')\n",
    "plt.axhline(0, color='gray', linewidth=1)\n",
    "plt.title('同业公司营业收入与净利润增长率对比图', fontsize=15)\n",
    "plt.xlabel('公司')\n",
    "plt.ylabel('增长率(%)')\n",
    "plt.xticks(x, peer_companies, rotation=0, ha='center')\n",
    "plt.legend()\n",
    "plt.grid(axis='y', alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "82db2af1",
   "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>指标</th>\n",
       "      <th>ROE</th>\n",
       "      <th>毛利率</th>\n",
       "      <th>净利润率</th>\n",
       "      <th>营业收入增长率</th>\n",
       "      <th>净利润增长率</th>\n",
       "      <th>平均排名</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>华洋赛车</th>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>春风动力</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>涛涛车业</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绿通科技</th>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>九号公司-WD</th>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱玛科技</th>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>钱江摩托</th>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>7</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>隆鑫通用</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>千里科技</th>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新日股份</th>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宗申动力</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>8</td>\n",
       "      <td>9</td>\n",
       "      <td>11</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信隆健康</th>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "指标       ROE  毛利率  净利润率  营业收入增长率  净利润增长率  平均排名\n",
       "华洋赛车       1    6     3        2       6   3.6\n",
       "春风动力       5    3     6        1       5   4.0\n",
       "涛涛车业       4    1     2        5       8   4.0\n",
       "绿通科技       3    2     1        6      10   4.4\n",
       "九号公司-WD    6    4     7        3       2   4.4\n",
       "爱玛科技       2    9     5        7       4   5.4\n",
       "钱江摩托       7    5     4       10       7   6.6\n",
       "隆鑫通用       8    8     9        8       9   8.4\n",
       "千里科技      12   12    12        4       3   8.6\n",
       "新日股份      11   10    11       12       1   9.0\n",
       "宗申动力      10   11     8        9      11   9.8\n",
       "信隆健康       9    7    10       11      12   9.8"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rank_indicators = ['ROE', '毛利率', '净利润率', '营业收入增长率', '净利润增长率']\n",
    "peer_rank = peer_compare[rank_indicators].rank(ascending=False, method='min').astype(int)\n",
    "peer_rank['平均排名'] = peer_rank.mean(axis=1).round(2)\n",
    "peer_rank = peer_rank.sort_values('平均排名')\n",
    "peer_rank"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13f219d6",
   "metadata": {},
   "source": [
    "### 同业比较分析结论\n",
    "\n",
    "从全部摩托车行业上市公司对比结果看，本部分共选取 12 家公司进行横向比较。根据 2021—2025 年核心财务指标均值排名，春风动力的平均排名为第 4.00 名，在全部样本公司中处于行业前列。华洋赛车平均排名为第 3.60 名，综合表现暂居第一；春风动力与涛涛车业平均排名相同，整体竞争力较强。\n",
    "\n",
    "分指标来看，春风动力在营业收入增长率方面排名第 1，说明公司收入扩张能力在行业中最为突出；毛利率排名第 3，表明其产品盈利空间和定价能力较强；ROE 和净利润增长率均排名第 5，仍处于行业中上水平。相对来看，春风动力的净利润率排名第 6，低于绿通科技、涛涛车业、华洋赛车、钱江摩托和爱玛科技，说明公司在费用控制和利润转化效率方面仍有提升空间。\n",
    "\n",
    "总体而言，春风动力在全部同业公司中具有较强的成长性和盈利能力优势，尤其体现在营业收入增长率和毛利率方面。但与行业内净利润率较高的公司相比，春风动力仍需进一步提高成本费用控制能力，增强收入增长向净利润增长的转化效果。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "876151ed",
   "metadata": {},
   "source": [
    "# 6.综合评价与分析——获取综合评分（0.4×趋势评分+0.6×同业评分）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "194ebd7d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T01:26:09.872436Z",
     "start_time": "2026-05-28T01:26:09.605840Z"
    }
   },
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>公司名称</th>\n",
       "      <th>毛利率</th>\n",
       "      <th>营业利润率</th>\n",
       "      <th>净利润率</th>\n",
       "      <th>ROE</th>\n",
       "      <th>存货周转率</th>\n",
       "      <th>总资产周转率</th>\n",
       "      <th>应收账款周转率</th>\n",
       "      <th>流动比率</th>\n",
       "      <th>速动比率</th>\n",
       "      <th>资产负债率</th>\n",
       "      <th>营业收入增长率</th>\n",
       "      <th>营业利润增长率</th>\n",
       "      <th>净利润增长率</th>\n",
       "      <th>趋势评分</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>钱江摩托</th>\n",
       "      <td>50.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>61.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宗申动力</th>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>53.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信隆健康</th>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绿通科技</th>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>40.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>涛涛车业</th>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>53.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>千里科技</th>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>57.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>春风动力</th>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>48.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱玛科技</th>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>51.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>隆鑫通用</th>\n",
       "      <td>75.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>67.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新日股份</th>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>53.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>九号公司-WD</th>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>57.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华洋赛车</th>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>38.46</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "公司名称       毛利率  营业利润率   净利润率    ROE  存货周转率  总资产周转率  应收账款周转率  流动比率  速动比率  \\\n",
       "钱江摩托      50.0  100.0  100.0   75.0   50.0    25.0     75.0  50.0  50.0   \n",
       "宗申动力      75.0   50.0   50.0   50.0   75.0    50.0     50.0  25.0  25.0   \n",
       "信隆健康      25.0    0.0    0.0    0.0   25.0    50.0     25.0  25.0  50.0   \n",
       "绿通科技      50.0   50.0   50.0   25.0   25.0    50.0     25.0  50.0  50.0   \n",
       "涛涛车业      75.0   75.0   75.0   25.0   50.0    25.0     25.0  50.0  50.0   \n",
       "千里科技      50.0   75.0   50.0   75.0   75.0    75.0     50.0   0.0  25.0   \n",
       "春风动力      50.0   75.0   75.0   75.0   50.0    25.0     25.0  25.0  25.0   \n",
       "爱玛科技     100.0   50.0   75.0   25.0   75.0    25.0     25.0  50.0  50.0   \n",
       "隆鑫通用      75.0  100.0   75.0  100.0   75.0    75.0     75.0  25.0  50.0   \n",
       "新日股份      75.0   50.0   50.0   50.0   50.0    50.0     50.0  50.0  50.0   \n",
       "九号公司-WD  100.0   75.0   75.0   75.0   50.0    50.0     50.0   0.0  50.0   \n",
       "华洋赛车      50.0   25.0   25.0    0.0   50.0    25.0     25.0  50.0  50.0   \n",
       "\n",
       "公司名称     资产负债率  营业收入增长率  营业利润增长率  净利润增长率   趋势评分  \n",
       "钱江摩托      50.0     50.0     75.0    50.0  61.54  \n",
       "宗申动力      50.0     50.0     75.0    75.0  53.85  \n",
       "信隆健康      50.0     25.0     25.0    25.0  25.00  \n",
       "绿通科技      50.0     50.0     25.0    25.0  40.38  \n",
       "涛涛车业      50.0     50.0     75.0    75.0  53.85  \n",
       "千里科技      75.0     75.0     50.0    75.0  57.69  \n",
       "春风动力      75.0     50.0     25.0    50.0  48.08  \n",
       "爱玛科技      25.0     75.0     50.0    50.0  51.92  \n",
       "隆鑫通用      75.0     50.0     50.0    50.0  67.31  \n",
       "新日股份      50.0     75.0     50.0    50.0  53.85  \n",
       "九号公司-WD  100.0     50.0     25.0    50.0  57.69  \n",
       "华洋赛车      50.0     50.0     50.0    50.0  38.46  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#趋势评分\n",
    "# 首先设置一个设置好行索引的空表\n",
    "score_sheet_trend = pd.read_excel('春风动力'+'.xlsx',sheet_name = '财务比率表').rename(columns={'Unnamed: 0': '公司名称'}).set_index('公司名称').iloc[:,0:0] #iloc切片\n",
    "score_sheet_trend \n",
    "\n",
    "for comp in mtc_name:\n",
    "    # 读取财务比率表数据\n",
    "    df_ratio = pd.read_excel(comp+'.xlsx',sheet_name='财务比率表')\n",
    "    df_ratio = df_ratio.rename(columns={'Unnamed: 0': '公司名称'})  # 第一列列名是unnamed:0,这里换成“公司名称”\n",
    "    df_ratio = df_ratio.set_index('公司名称')\n",
    "    data = df_ratio.T\n",
    "    # 进行评分\n",
    "    scores = []\n",
    "    for i in range(len(df_ratio)): #遍历所有的比率\n",
    "        n = 0\n",
    "        for j in range(len(data)-1): #遍历某一比率列的每一行并返回score\n",
    "            if np.isinf(data.iloc[j,i]) == True:\n",
    "                n = n+1\n",
    "            elif data.iloc[j,i]<data.iloc[j+1,i]:\n",
    "                n = n+1\n",
    "        # 分数标准化为100分\n",
    "        n = n/(len(data)-1) * 100\n",
    "        scores.append(n)   \n",
    "    score_sheet_trend[comp] = scores\n",
    "score_sheet_trend = score_sheet_trend.T\n",
    "trend_scores = round(score_sheet_trend.T.mean(),2)\n",
    "score_sheet_trend['趋势评分'] = trend_scores\n",
    "score_sheet_trend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "5a533baa",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T01:26:12.068108Z",
     "start_time": "2026-05-28T01:26:11.814035Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>公司名称</th>\n",
       "      <th>毛利率</th>\n",
       "      <th>营业利润率</th>\n",
       "      <th>净利润率</th>\n",
       "      <th>ROE</th>\n",
       "      <th>存货周转率</th>\n",
       "      <th>总资产周转率</th>\n",
       "      <th>应收账款周转率</th>\n",
       "      <th>流动比率</th>\n",
       "      <th>速动比率</th>\n",
       "      <th>资产负债率</th>\n",
       "      <th>营业收入增长率</th>\n",
       "      <th>营业利润增长率</th>\n",
       "      <th>净利润增长率</th>\n",
       "      <th>同业评分</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>钱江摩托</th>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>57.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宗申动力</th>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>48.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信隆健康</th>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>46.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绿通科技</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>71.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>涛涛车业</th>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>69.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>千里科技</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>36.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>春风动力</th>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>78.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱玛科技</th>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>73.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>隆鑫通用</th>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>61.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新日股份</th>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>53.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>九号公司-WD</th>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>73.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华洋赛车</th>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>80.77</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "公司名称     毛利率  营业利润率  净利润率  ROE  存货周转率  总资产周转率  应收账款周转率  流动比率  速动比率  资产负债率  \\\n",
       "钱江摩托      75     75    75   50     25      25       75    75    75     50   \n",
       "宗申动力      25     50    50   25     75      50       25    75    75     75   \n",
       "信隆健康      50     25    25   50     50      25       25    75    75     50   \n",
       "绿通科技     100    100   100  100     50      50       50   100   100     25   \n",
       "涛涛车业     100    100   100   75     25      50       50   100   100     25   \n",
       "千里科技      25     25    25   25     25      25       25    25    25     50   \n",
       "春风动力     100     75    75   75     75     100       75    50    50    100   \n",
       "爱玛科技      50     75    75  100    100      75      100    25    25    100   \n",
       "隆鑫通用      50     50    50   50    100      75       50   100   100     25   \n",
       "新日股份      25     25    25   25    100     100      100    25    25    100   \n",
       "九号公司-WD   75     50    50   75     75      75       75    50    50     75   \n",
       "华洋赛车      75    100   100  100     50     100      100    50    50     75   \n",
       "\n",
       "公司名称     营业收入增长率  营业利润增长率  净利润增长率   同业评分  \n",
       "钱江摩托          25       75      50  57.69  \n",
       "宗申动力          50       25      25  48.08  \n",
       "信隆健康          25      100      25  46.15  \n",
       "绿通科技          75       50      25  71.15  \n",
       "涛涛车业          75       50      50  69.23  \n",
       "千里科技          75       25     100  36.54  \n",
       "春风动力         100       75      75  78.85  \n",
       "爱玛科技          50      100      75  73.08  \n",
       "隆鑫通用          50       50      50  61.54  \n",
       "新日股份          25       25     100  53.85  \n",
       "九号公司-WD      100      100     100  73.08  \n",
       "华洋赛车         100       75      75  80.77  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 同业评分\n",
    "ratio_ind = pd.DataFrame()\n",
    "for name in mtc_name:\n",
    "    # 读取财务比率表数据\n",
    "    df_ratio = pd.read_excel(name+'.xlsx',sheet_name='财务比率表')\n",
    "    df_ratio = df_ratio.rename(columns={'Unnamed: 0': '公司名称'})  # 第一列列名是unnamed:0,这里换成“公司名称”\n",
    "    df_ratio = df_ratio.set_index('公司名称')\n",
    "    meanvalue = df_ratio.T.mean()\n",
    "    df_ratio[name]=meanvalue\n",
    "    ratio_ind = pd.concat([ratio_ind,df_ratio[[name]].T])\n",
    "\n",
    "score_sheet = ratio_ind.T\n",
    "standard = ratio_ind.describe()\n",
    "\n",
    "for i in range(len(ratio_ind)):\n",
    "    scores = []\n",
    "    for j in range(len(ratio_ind.T)):\n",
    "        if np.isinf(ratio_ind.iloc[i,j]) == True:\n",
    "            n=100\n",
    "        elif ratio_ind.iloc[i,j]>standard.loc['75%'][j]:\n",
    "            n = 100\n",
    "        elif standard.loc['50%'][j]<ratio_ind.iloc[i,j]<=standard.loc['75%'][j]:\n",
    "            n = 75\n",
    "        elif standard.loc['25%'][j]<ratio_ind.iloc[i,j]<=standard.loc['50%'][j]:\n",
    "            n = 50\n",
    "        else:\n",
    "            n = 25\n",
    "        scores.append(n)\n",
    "    score_sheet[mtc_name[i]]=scores\n",
    "ty_score = round(score_sheet.mean(),2)\n",
    "score_sheet_ty = score_sheet.T\n",
    "score_sheet_ty['同业评分']=ty_score\n",
    "score_sheet_ty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "f0fafb4a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T01:26:14.189414Z",
     "start_time": "2026-05-28T01:26:14.107345Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>公司名称</th>\n",
       "      <th>毛利率(趋势得分)</th>\n",
       "      <th>营业利润率(趋势得分)</th>\n",
       "      <th>净利润率(趋势得分)</th>\n",
       "      <th>ROE(趋势得分)</th>\n",
       "      <th>存货周转率(趋势得分)</th>\n",
       "      <th>总资产周转率(趋势得分)</th>\n",
       "      <th>应收账款周转率(趋势得分)</th>\n",
       "      <th>流动比率(趋势得分)</th>\n",
       "      <th>速动比率(趋势得分)</th>\n",
       "      <th>资产负债率(趋势得分)</th>\n",
       "      <th>...</th>\n",
       "      <th>总资产周转率(同业得分)</th>\n",
       "      <th>应收账款周转率(同业得分)</th>\n",
       "      <th>流动比率(同业得分)</th>\n",
       "      <th>速动比率(同业得分)</th>\n",
       "      <th>资产负债率(同业得分)</th>\n",
       "      <th>营业收入增长率(同业得分)</th>\n",
       "      <th>营业利润增长率(同业得分)</th>\n",
       "      <th>净利润增长率(同业得分)</th>\n",
       "      <th>同业评分</th>\n",
       "      <th>综合评分</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>九号公司-WD</th>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>...</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>73.08</td>\n",
       "      <td>66.924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>春风动力</th>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>78.85</td>\n",
       "      <td>66.542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱玛科技</th>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>...</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>73.08</td>\n",
       "      <td>64.616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>隆鑫通用</th>\n",
       "      <td>75.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>...</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>61.54</td>\n",
       "      <td>63.848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>华洋赛车</th>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>100</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>80.77</td>\n",
       "      <td>63.846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>涛涛车业</th>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>69.23</td>\n",
       "      <td>63.078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>钱江摩托</th>\n",
       "      <td>50.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>57.69</td>\n",
       "      <td>59.230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>绿通科技</th>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>71.15</td>\n",
       "      <td>58.842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新日股份</th>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>53.85</td>\n",
       "      <td>53.850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>宗申动力</th>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>48.08</td>\n",
       "      <td>50.388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>千里科技</th>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>50</td>\n",
       "      <td>75</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>36.54</td>\n",
       "      <td>45.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信隆健康</th>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>75</td>\n",
       "      <td>75</td>\n",
       "      <td>50</td>\n",
       "      <td>25</td>\n",
       "      <td>100</td>\n",
       "      <td>25</td>\n",
       "      <td>46.15</td>\n",
       "      <td>37.690</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "公司名称     毛利率(趋势得分)  营业利润率(趋势得分)  净利润率(趋势得分)  ROE(趋势得分)  存货周转率(趋势得分)  \\\n",
       "九号公司-WD      100.0         75.0        75.0       75.0         50.0   \n",
       "春风动力          50.0         75.0        75.0       75.0         50.0   \n",
       "爱玛科技         100.0         50.0        75.0       25.0         75.0   \n",
       "隆鑫通用          75.0        100.0        75.0      100.0         75.0   \n",
       "华洋赛车          50.0         25.0        25.0        0.0         50.0   \n",
       "涛涛车业          75.0         75.0        75.0       25.0         50.0   \n",
       "钱江摩托          50.0        100.0       100.0       75.0         50.0   \n",
       "绿通科技          50.0         50.0        50.0       25.0         25.0   \n",
       "新日股份          75.0         50.0        50.0       50.0         50.0   \n",
       "宗申动力          75.0         50.0        50.0       50.0         75.0   \n",
       "千里科技          50.0         75.0        50.0       75.0         75.0   \n",
       "信隆健康          25.0          0.0         0.0        0.0         25.0   \n",
       "\n",
       "公司名称     总资产周转率(趋势得分)  应收账款周转率(趋势得分)  流动比率(趋势得分)  速动比率(趋势得分)  资产负债率(趋势得分)  \\\n",
       "九号公司-WD          50.0           50.0         0.0        50.0        100.0   \n",
       "春风动力             25.0           25.0        25.0        25.0         75.0   \n",
       "爱玛科技             25.0           25.0        50.0        50.0         25.0   \n",
       "隆鑫通用             75.0           75.0        25.0        50.0         75.0   \n",
       "华洋赛车             25.0           25.0        50.0        50.0         50.0   \n",
       "涛涛车业             25.0           25.0        50.0        50.0         50.0   \n",
       "钱江摩托             25.0           75.0        50.0        50.0         50.0   \n",
       "绿通科技             50.0           25.0        50.0        50.0         50.0   \n",
       "新日股份             50.0           50.0        50.0        50.0         50.0   \n",
       "宗申动力             50.0           50.0        25.0        25.0         50.0   \n",
       "千里科技             75.0           50.0         0.0        25.0         75.0   \n",
       "信隆健康             50.0           25.0        25.0        50.0         50.0   \n",
       "\n",
       "公司名称     ...  总资产周转率(同业得分)  应收账款周转率(同业得分)  流动比率(同业得分)  速动比率(同业得分)  \\\n",
       "九号公司-WD  ...            75             75          50          50   \n",
       "春风动力     ...           100             75          50          50   \n",
       "爱玛科技     ...            75            100          25          25   \n",
       "隆鑫通用     ...            75             50         100         100   \n",
       "华洋赛车     ...           100            100          50          50   \n",
       "涛涛车业     ...            50             50         100         100   \n",
       "钱江摩托     ...            25             75          75          75   \n",
       "绿通科技     ...            50             50         100         100   \n",
       "新日股份     ...           100            100          25          25   \n",
       "宗申动力     ...            50             25          75          75   \n",
       "千里科技     ...            25             25          25          25   \n",
       "信隆健康     ...            25             25          75          75   \n",
       "\n",
       "公司名称     资产负债率(同业得分)  营业收入增长率(同业得分)  营业利润增长率(同业得分)  净利润增长率(同业得分)   同业评分  \\\n",
       "九号公司-WD           75            100            100           100  73.08   \n",
       "春风动力             100            100             75            75  78.85   \n",
       "爱玛科技             100             50            100            75  73.08   \n",
       "隆鑫通用              25             50             50            50  61.54   \n",
       "华洋赛车              75            100             75            75  80.77   \n",
       "涛涛车业              25             75             50            50  69.23   \n",
       "钱江摩托              50             25             75            50  57.69   \n",
       "绿通科技              25             75             50            25  71.15   \n",
       "新日股份             100             25             25           100  53.85   \n",
       "宗申动力              75             50             25            25  48.08   \n",
       "千里科技              50             75             25           100  36.54   \n",
       "信隆健康              50             25            100            25  46.15   \n",
       "\n",
       "公司名称       综合评分  \n",
       "九号公司-WD  66.924  \n",
       "春风动力     66.542  \n",
       "爱玛科技     64.616  \n",
       "隆鑫通用     63.848  \n",
       "华洋赛车     63.846  \n",
       "涛涛车业     63.078  \n",
       "钱江摩托     59.230  \n",
       "绿通科技     58.842  \n",
       "新日股份     53.850  \n",
       "宗申动力     50.388  \n",
       "千里科技     45.000  \n",
       "信隆健康     37.690  \n",
       "\n",
       "[12 rows x 29 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_sheet = score_sheet_trend.join(score_sheet_ty, lsuffix='(趋势得分)', rsuffix='(同业得分)')\n",
    "score_sheet['综合评分']=0.4*score_sheet['趋势评分']+0.6*score_sheet['同业评分']\n",
    "score_sheet = score_sheet.sort_values(by='综合评分',ascending=False)\n",
    "score_sheet.to_excel('综合评分表.xlsx')\n",
    "score_sheet"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdd5d2b0",
   "metadata": {},
   "source": [
    "# 6.综合评价与分析——数据可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "82ac97be",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T01:26:17.292207Z",
     "start_time": "2026-05-28T01:26:17.018919Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "plt.figure(figsize=(14, 8))\n",
    "\n",
    "# 堆叠柱状图：趋势得分 + 同业得分\n",
    "bottom = np.zeros(len(score_sheet))\n",
    "\n",
    "bars1 = plt.bar(score_sheet.index,score_sheet['趋势评分'],label='趋势评分',color='lightgreen',edgecolor='white',linewidth=0.8)\n",
    "\n",
    "bottom += score_sheet['趋势评分']\n",
    "\n",
    "bars2 = plt.bar(score_sheet.index,score_sheet['同业评分'],label='同业评分',bottom=bottom,color='gold',edgecolor='white',linewidth=0.8)\n",
    "\n",
    "plt.title('摩托车行业上市公司财务综合评分对比（趋势评分与同业评分）', fontsize=16)\n",
    "plt.ylabel('趋势评分与同业评分', fontsize=12)\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "plt.legend(fontsize=12)\n",
    "plt.grid(axis='y', alpha=0.3)\n",
    "\n",
    "# 添加数值标签\n",
    "# 1. 趋势评分（绿色底部柱子）：显示在自身柱子中间\n",
    "for bar in bars1:\n",
    "    height = bar.get_height()\n",
    "    plt.text(\n",
    "        bar.get_x() + bar.get_width()/2,  # 水平居中\n",
    "        height / 2,                       # 垂直居中\n",
    "        f'{height:.2f}',\n",
    "        ha='center', va='center', fontsize=12, fontweight='bold'\n",
    "    )\n",
    "\n",
    "# 2. 同业评分（黄色上部柱子）：显示在自身柱子中间\n",
    "for i, bar in enumerate(bars2):\n",
    "    height = bar.get_height()\n",
    "    # 同业柱子的中间位置 = 趋势高度 + 自身高度/2\n",
    "    y_pos = score_sheet['趋势评分'].iloc[i] + height / 2\n",
    "    plt.text(\n",
    "        bar.get_x() + bar.get_width()/2,\n",
    "        y_pos,\n",
    "        f'{height:.2f}',\n",
    "        ha='center', va='center', fontsize=12, fontweight='bold'\n",
    "    )\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "0ee8f39a",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-05-28T01:26:19.775304Z",
     "start_time": "2026-05-28T01:26:19.527984Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "plt.figure(figsize=(14, 8))\n",
    "\n",
    "# 柱状图：综合评分\n",
    "bars = plt.bar(score_sheet.index,score_sheet['综合评分'],label='趋势评分 (权重40%) 与同业评分 (权重60%)',color='lightblue',edgecolor='white',linewidth=0.8)\n",
    "\n",
    "\n",
    "plt.title('摩托车行业上市公司财务综合评分对比（综合评分）', fontsize=16)\n",
    "plt.ylabel('综合评分', fontsize=12)\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "plt.legend(fontsize=12)\n",
    "plt.grid(axis='y', alpha=0.3)\n",
    "\n",
    "# 添加数值标签\n",
    "for bar in bars:\n",
    "    height = bar.get_height()\n",
    "    plt.text(bar.get_x() + bar.get_width()/2., height + 0.5,\n",
    "             f'{height:.2f}',\n",
    "             ha='center', va='bottom', fontsize=12)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}