20220805

.ipynb_checkpoints/中医体质管理-checkpoint.ipynb

@@ -0,0 +1,100 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "86c59eaa-b1fd-47f3-aa0d-3ad3626df3bf",
+   "metadata": {},
+   "source": [
+    "# 中医体质管理"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e791846d-699f-4803-b898-bda8f1a30dd2",
+   "metadata": {},
+   "source": [
+    "## 中医体质数据管理"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19cd094e-8228-4f21-9897-9e8bef990d4e",
+   "metadata": {},
+   "source": [
+    "### 体质监测数据生成"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "1f58bd08-d20b-4a76-a841-ac7e132a54b7",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-08-05T05:39:03.670486Z",
+     "iopub.status.busy": "2022-08-05T05:39:03.669966Z",
+     "iopub.status.idle": "2022-08-05T05:39:03.705022Z",
+     "shell.execute_reply": "2022-08-05T05:39:03.703508Z",
+     "shell.execute_reply.started": "2022-08-05T05:39:03.670438Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ok\n"
+     ]
+    }
+   ],
+   "source": [
+    "import re\n",
+    "import json\n",
+    "\n",
+    "file_name = 'data/132.txt'\n",
+    "list1 =[]\n",
+    "dict1 = {}\n",
+    "with open(file_name,'r') as fl:\n",
+    "    for l in fl:\n",
+    "        list2 = []\n",
+    "        l = re.sub('[\\r\\n\\f ]{1,}', '', l)\n",
+    "        list2 = l.split(',')\n",
+    "        if list2[0] != '' and list2[5] != '':\n",
+    "            dict1[list2[0]] = [list2[1],list2[2],list2[3],list2[4],list2[5]+list2[6]]\n",
+    "filename = 'data/132中医体质.json'\n",
+    "with open(filename,'w') as fl:\n",
+    "    json.dump(dict1, fl) \n",
+    "print('ok')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "400f6c4b-8a67-4872-a912-a0aad86e923c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

体质检测管理.ipynb

@@ -14,6 +14,8 @@
    "cell_type": "markdown",
    "id": "2a85feec-695b-4ea8-8093-91a59ed34c7f",
    "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": [],
     "toc-hr-collapsed": true
    },
    "source": [
@@ -528,7 +530,10 @@
   {
    "cell_type": "markdown",
    "id": "54d4790d-973f-4ee6-abff-3d5ff962de23",
-   "metadata": {},
+   "metadata": {
+    "tags": [],
+    "toc-hr-collapsed": true
+   },
    "source": [
     "## 获取测试人员名单导入数据库"
    ]
@@ -1442,12 +1447,24 @@
     "#print(dict1)\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "3711130b-59e3-4844-ac31-234ba77cd46c",
+   "metadata": {
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": [],
+    "toc-hr-collapsed": true
+   },
+   "source": [
+    "## 脊柱症状统计"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "c67fc14e-ccf8-41c5-a0f8-0c3a664eb484",
    "metadata": {},
    "source": [
-    "## 脊椎代码表导入"
+    "### 脊椎代码表导入"
    ]
   },
   {
@@ -1479,7 +1496,7 @@
    "id": "36717021-5c0e-40d6-8988-dfe8ec309275",
    "metadata": {},
    "source": [
-    "## 脊椎症状自我诊断表导入"
+    "### 脊椎症状自我诊断表导入"
    ]
   },
   {
@@ -1522,16 +1539,6 @@
     "print('ok')"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "3711130b-59e3-4844-ac31-234ba77cd46c",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## 脊柱症状统计"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "ae25fffb-4682-49b1-90aa-218504ac88d7",
@@ -2281,7 +2288,9 @@
   {
    "cell_type": "markdown",
    "id": "f9e61ba9-38f8-4b61-bf1e-4e7bbde4f32c",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "## 心理健康量表统计导入"
    ]
@@ -2323,7 +2332,7 @@
    "id": "f400d470-d51e-4226-a1c4-54ac711c7f38",
    "metadata": {},
    "source": [
-    "## 查询心理健康量表编号重复"
+    "### 查询心理健康量表编号重复"
    ]
   },
   {
@@ -2357,7 +2366,7 @@
    "id": "641cc9a9-45b2-4b81-953c-75d3a27e35d5",
    "metadata": {},
    "source": [
-    "## 统计导入JSON文件记录数"
+    "### 统计导入JSON文件记录数"
    ]
   },
   {

文件操作.ipynb

@@ -17,16 +17,18 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "import os,sys,shutil\n",
     "import openpyxl\n",
     "import math\n",
     "\n",
-    "fi_xls = os.getcwd()+'/file/中国石油化工股份有限公司安庆炼化分公司员工在职人员名单.xlsx'\n",
+    "fi_xls = os.getcwd()+'/file/高新区.xlsx'\n",
     "fi_name = {}\n",
-    "fi_path = os.getcwd()+'/file/210924'\n",
+    "fi_path = os.getcwd()+'/file/220720'\n",
     "old = []\n",
     "new = []\n",
     "dict1 = {}\n",
@@ -35,19 +37,20 @@
     "sheet = wb.active\n",
     "depart = []\n",
     "for n in range(2,sheet.max_row+1):\n",
-    "    \n",
+    "    if sheet.cell(n,3).value is not None: \n",
-    "    m_name = sheet.cell(n,1).value.strip()\n",
+    "        m_name = sheet.cell(n,6).value.strip()\n",
-    "    m_depart = sheet.cell(n,5).value\n",
+    "        m_depart = sheet.cell(n,3).value.strip()           \n",
-    "    if m_depart not in depart:\n",
+    "        depart.append(m_depart)    \n",
-    "        depart.append(sheet.cell(n,5).value)\n",
+    "        dict1[int(sheet.cell(n,4).value)] = [m_name,m_depart]\n",
-    "    dict1[int(m_name.split('.')[0])] = [sheet.cell(n,2).value.strip(),sheet.cell(n,5).value.strip()]\n",
     "    #print()\n",
     "# 创建部门办公室    \n",
-    "#m_path = fi_path = os.getcwd()+'/file/210924/new'\n",
+    "m_path = os.getcwd()+'/file/220720/new'\n",
-    "#for pn in depart:\n",
+    "for pn in depart:\n",
-    "#    if not os.path.exists(m_path + '/' + pn):\n",
+    "    if not os.path.exists(m_path + '/' + pn):\n",
-    "#        os.mkdir(m_path + '/' + pn)\n",
+    "        os.mkdir(m_path + '/' + pn)\n",
     "#print(dict1)\n",
+    "\n",
+    "\n",
     "fl=os.listdir(fi_path)\n",
     "for fn in fl:\n",
     "    if os.path.isfile(fi_path + '/' + fn):\n",
@@ -56,17 +59,17 @@
     "    #print(fn)\n",
     "old.sort()\n",
     "    #print(str(nfn)+'.pdf')\n",
-    "'''\n",
+    "\n",
     "for n in old:\n",
     "    \n",
     "    o_name = f'{fi_path}/{n}.pdf'\n",
-    "    n_name = f'{fi_path}/new/{dict1[n][1]}/{dict1[n][0]}.pdf'\n",
+    "    n_name = f'{fi_path}/new/{dict1[n][1]}/{str(n).rjust(5,\"0\")}-{dict1[n][0]}.pdf'\n",
     "    if not os.path.exists(n_name):\n",
     "        shutil.copyfile(o_name,n_name)\n",
     "        print(n_name)\n",
     "#print(old)\n",
-    "'''\n",
+    "\n",
-    "print(dict1)"
+    "#print(dict1)"
    ]
   },
   {

文件管理1.ipynb

@@ -29,8 +29,8 @@
     "import openpyxl\n",
     "import math\n",
     "\n",
-    "fi_xls = os.getcwd() + '/data/岳阳兴长.xlsx'\n",
+    "fi_xls = os.getcwd() + '/data/高新区.xlsx'\n",
-    "fi_path = os.getcwd() + '/file/220427'\n",
+    "fi_path = os.getcwd() + '/file/220720'\n",
     "old = []\n",
     "dict1 = {}\n",
     "\n",
@@ -126,9 +126,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 38,
    "id": "a34c9f6b-4ef3-4678-89bb-8b692e183968",
    "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-07-31T13:49:49.854261Z",
+     "iopub.status.busy": "2022-07-31T13:49:49.853622Z",
+     "iopub.status.idle": "2022-07-31T13:49:50.369847Z",
+     "shell.execute_reply": "2022-07-31T13:49:50.368685Z",
+     "shell.execute_reply.started": "2022-07-31T13:49:49.854177Z"
+    },
     "tags": []
    },
    "outputs": [],

高考志愿管理.ipynb

@@ -95,15 +95,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-15T07:00:27.890983Z",
-     "iopub.status.busy": "2022-06-15T07:00:27.890444Z",
-     "iopub.status.idle": "2022-06-15T07:00:28.430955Z",
-     "shell.execute_reply": "2022-06-15T07:00:28.429949Z",
-     "shell.execute_reply.started": "2022-06-15T07:00:27.890936Z"
-    },
     "tags": []
    },
    "outputs": [],
@@ -135,65 +128,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-15T08:26:50.903511Z",
-     "iopub.status.busy": "2022-06-15T08:26:50.902972Z",
-     "iopub.status.idle": "2022-06-15T08:26:50.972239Z",
-     "shell.execute_reply": "2022-06-15T08:26:50.971224Z",
-     "shell.execute_reply.started": "2022-06-15T08:26:50.903463Z"
-    },
     "tags": []
    },
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "河北工业职业技术大学导入成功！\n",
-      "河北科技工程职业技术大学导入成功！\n",
-      "河北石油职业技术大学导入成功！\n",
-      "邢台应用技术职业学院导入成功！\n",
-      "山西工程科技职业大学导入成功！\n",
-      "吉林通用航空职业技术学院导入成功！\n",
-      "通化医药健康职业学院导入成功！\n",
-      "上海南湖职业技术学院导入成功！\n",
-      "浙江药科职业大学导入成功！\n",
-      "浙江金华科贸职业技术学院导入成功！\n",
-      "宿州航空职业学院导入成功！\n",
-      "和君职业学院导入成功！\n",
-      "滨州科技职业学院导入成功！\n",
-      "洛阳文化旅游职业学院导入成功！\n",
-      "周口文理职业学院导入成功！\n",
-      "信阳艺术职业学院导入成功！\n",
-      "郑州城建职业学院导入成功！\n",
-      "郑州医药健康职业学院导入成功！\n",
-      "湖北孝感美珈职业学院导入成功！\n",
-      "广州幼儿师范高等专科学校导入成功！\n",
-      "广东汕头幼儿师范高等专科学校导入成功！\n",
-      "广东梅州职业技术学院导入成功！\n",
-      "广东潮州卫生健康职业学院导入成功！\n",
-      "广东云浮中医药职业学院导入成功！\n",
-      "广东肇庆航空职业学院导入成功！\n",
-      "广西农业职业技术大学导入成功！\n",
-      "防城港职业技术学院导入成功！\n",
-      "广西信息职业技术学院导入成功！\n",
-      "广西农业工程职业技术学院导入成功！\n",
-      "北海康养职业学院导入成功！\n",
-      "重庆工信职业学院导入成功！\n",
-      "甘孜职业学院导入成功！\n",
-      "自贡职业技术学院导入成功！\n",
-      "贵阳康养职业大学导入成功！\n",
-      "贵州文化旅游职业学院导入成功！\n",
-      "宝鸡中北职业学院导入成功！\n",
-      "兰州石化职业技术大学导入成功！\n",
-      "兰州资源环境职业技术大学导入成功！\n",
-      "兰州航空职业技术学院导入成功！\n",
-      "白银希望职业技术学院导入成功！\n"
-     ]
-    }
-   ],
    "source": [
     "import openpyxl\n",
     "import json\n",
@@ -548,6 +487,147 @@
     "print(list2)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2022年高考选科数据分析"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2022年选科数据导入"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "import pymongo\n",
+    "\n",
+    "filename = 'data/2022招生计划（汇总）.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    m_xx = json.load(fl)\n",
+    "#print(m_xx)\n",
+    "xuanke = []\n",
+    "dict1 = {}\n",
+    "dict2 = {}\n",
+    "dict2['0'] = '不限'\n",
+    "dict2['1'] = '物理和化学和生物'\n",
+    "dict2['2'] = '思想政治和历史和地理'\n",
+    "dict3 = {}\n",
+    "for k, v in m_xx.items():\n",
+    "    col_code = k\n",
+    "    col_name = v['学校名称']\n",
+    "    for item in v['专业']:\n",
+    "        m_code = col_code+'-'+item['unit_code']\n",
+    "        m_name = item['unit_name']\n",
+    "        m_xuanke = item['xuanke'].strip()\n",
+    "        if m_xuanke not in xuanke:\n",
+    "            xuanke.append(m_xuanke)\n",
+    "        dict1[m_code] = [m_name,m_xuanke]\n",
+    "fl_name = 'data/2022年选科分析表.json'\n",
+    "with open(fl_name,'w') as fl:\n",
+    "    json.dump(dict1,fl)\n",
+    "xuanke.remove('不限')\n",
+    "xuanke.remove('物理和化学和生物')\n",
+    "xuanke.remove('思想政治和历史和地理')\n",
+    "print(xuanke)\n",
+    "dict3['不限'] = [1,'0',['物理','化学','生物','思想政治','历史','地理']]\n",
+    "dict3['物理和化学和生物'] = [2,'1',['物理','化学','生物']]\n",
+    "dict3['思想政治和历史和地理'] = [3,'1',['思想政治','历史','地理']]\n",
+    "i = 4\n",
+    "for item in xuanke:\n",
+    "    #dict3[str(i)].setdault({})\n",
+    "    if '和' in item:\n",
+    "        mx = item.split('和')\n",
+    "        dict3[item] = [i,'1',mx]\n",
+    "    elif '或' in item:\n",
+    "        mx = item.split('或')\n",
+    "        dict3[item] = [i,'0',mx]\n",
+    "    else:\n",
+    "        dict3[item] = [i,'0',[item]]\n",
+    "    i+=1\n",
+    "fl_name = 'data/选科代码表.json'\n",
+    "with open(fl_name,'w') as fl:\n",
+    "    json.dump(dict3,fl)\n",
+    "print('ok!')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 选科数据导入Mysql"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-08-04T06:47:19.617840Z",
+     "iopub.status.busy": "2022-08-04T06:47:19.617316Z",
+     "iopub.status.idle": "2022-08-04T06:47:20.416287Z",
+     "shell.execute_reply": "2022-08-04T06:47:20.414857Z",
+     "shell.execute_reply.started": "2022-08-04T06:47:19.617790Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ok!\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pymysql\n",
+    "import json\n",
+    "\n",
+    "filename = 'data/选科代码表.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    dmb = json.load(fl)\n",
+    "\n",
+    "filename = 'data/2022年选科分析表.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    jhb = json.load(fl)    \n",
+    "list1 = []\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"root\",password = \"songyi\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "\n",
+    "sql = 'select college,speciality,rank_min from admission_2022 order by rank_min'\n",
+    "cursor.execute(sql)\n",
+    "results = cursor.fetchall()\n",
+    "for result in results:\n",
+    "    m_dm = result[0]+'-'+result[1]\n",
+    "    if m_dm in jhb.keys():\n",
+    "        m_xk = jhb[m_dm][1].strip()\n",
+    "        m_item = ','.join(dmb[m_xk][2])\n",
+    "        list1.append((result[0],result[1],str(dmb[m_xk][0]),m_item))\n",
+    "\n",
+    "sql = 'insert into zhiyuanfenxi (col_code,spe_code,zy_code,item) values (%s,%s,%s,%s)'\n",
+    "try:\n",
+    "    cursor.executemany(sql,list1)\n",
+    "    db.commit()\n",
+    "    print(\"ok!\")\n",
+    "except:\n",
+    "    # 如果发生错误则回滚\n",
+    "    print(\"error!\")\n",
+    "    db.rollback()   \n",
+    "\n",
+    "db.close()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

高考数据导入.ipynb

@@ -286,26 +286,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": null,
    "metadata": {
-    "execution": {
-     "iopub.execute_input": "2022-06-15T09:08:30.396155Z",
-     "iopub.status.busy": "2022-06-15T09:08:30.395636Z",
-     "iopub.status.idle": "2022-06-15T09:08:39.230104Z",
-     "shell.execute_reply": "2022-06-15T09:08:39.228838Z",
-     "shell.execute_reply.started": "2022-06-15T09:08:30.396108Z"
-    },
     "tags": []
    },
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "ok\n"
-     ]
-    }
-   ],
    "source": [
     "import pymysql\n",
     "import pymongo\n",
@@ -751,7 +736,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "## 导入2021年录取数据"
    ]
@@ -1005,6 +992,390 @@
     "db.close() "
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 导入2022年录取数据"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 导出2022年录取数据并生成分数"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import openpyxl\n",
+    "import json\n",
+    "\n",
+    "filename = 'data/17-22年一分一段表.json'\n",
+    "with open(filename,'r') as fl:\n",
+    "    m_xx = json.load(fl)\n",
+    "data = m_xx['2022']['z']\n",
+    "yfyd = {}\n",
+    "for k, v in data.items():\n",
+    "    list1 = []\n",
+    "    list1 = (v['min_rank'],v['max_rank'])\n",
+    "    yfyd[k] = list1\n",
+    "dict1 = {}\n",
+    "filename = 'data/山东省2022年普通类常规批第一次志愿投档情况表.xlsx'\n",
+    "wb = openpyxl.load_workbook(filename)\n",
+    "sheet = wb.active\n",
+    "data1 =list(sheet.values)\n",
+    "del data1[0:2]\n",
+    "m_num = 1\n",
+    "i = 1\n",
+    "for items in data1:\n",
+    "    m_rank = items[3]    \n",
+    "    list1 = []\n",
+    "    for k, v in yfyd.items():\n",
+    "        if m_rank >=v[1] and m_rank <=v[0]:\n",
+    "            m_num = int(k)\n",
+    "            break\n",
+    "    list1 = (items[0],items[1],items[2],items[3],m_num)\n",
+    "    dict1[i] = list1\n",
+    "    i += 1 \n",
+    "with open('data/2022.json','w') as fl2:\n",
+    "    json.dump(dict1,fl2) \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2022年录取数据导入mysql数据库"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pymysql\n",
+    "import json\n",
+    "\n",
+    "l_code = []\n",
+    "l_new = []\n",
+    "l_data = []\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"root\",password = \"songyi\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "\n",
+    "sql = 'select code from college'\n",
+    "cursor.execute(sql)\n",
+    "results = cursor.fetchall()\n",
+    "for result in results:\n",
+    "    l_code.append(result[0])\n",
+    "\n",
+    "with open('data/2022.json','r') as fl:\n",
+    "    m_xx = json.load(fl)\n",
+    "for k, v in m_xx.items():\n",
+    "    #code = v[1][:4]\n",
+    "    l_data.append([v[1][:4],v[0][:2],v[2],v[4],v[3]])\n",
+    "\n",
+    "sql = \"insert into admission_2022 (college,speciality,plan,num_min,rank_min,nian) values(%s,%s,%s,%s,%s,'2022')\"\n",
+    "try:\n",
+    "    cursor.executemany(sql,l_data)\n",
+    "    db.commit()\n",
+    "    print(\"已添加！\")\n",
+    "except:\n",
+    "    # 如果发生错误则回滚\n",
+    "    print(\"error!\")\n",
+    "    db.rollback()   \n",
+    "db.close() "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 整理2022年招生学校"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pymysql\n",
+    "import json\n",
+    "\n",
+    "l_code = []\n",
+    "l_new = []\n",
+    "l_data = []\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"root\",password = \"songyi\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "\n",
+    "sql = 'select code from college'\n",
+    "cursor.execute(sql)\n",
+    "results = cursor.fetchall()\n",
+    "for result in results:\n",
+    "    l_code.append(result[0])\n",
+    "\n",
+    "with open('data/2022.json','r') as fl:\n",
+    "    m_xx = json.load(fl)\n",
+    "for k, v in m_xx.items():\n",
+    "    code = v[1][:4]\n",
+    "    if code not in l_code:\n",
+    "        l_code.append(code)\n",
+    "        l_new.append([v[1][0:4],v[1][4:]])\n",
+    "    #l_data.append([v[1][:4],v[0][:2],v[2],v[4],v[3]])\n",
+    "sql = \"insert into college (code,name) values(%s,%s)\"\n",
+    "try:\n",
+    "    cursor.executemany(sql,l_new)\n",
+    "    db.commit()\n",
+    "    print(\"已添加！\")\n",
+    "except:\n",
+    "    # 如果发生错误则回滚\n",
+    "    print(\"error!\")\n",
+    "    db.rollback()   \n",
+    "db.close() "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 整理2022年新增招生学校"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pymongo\n",
+    "import decimal\n",
+    "import json\n",
+    "\n",
+    "\n",
+    "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
+    "mydb = myclient[\"gaokao\"]\n",
+    "mycol = mydb[\"college_2021\"]\n",
+    "mycol1 = mydb[\"admission_2021\"]\n",
+    "\n",
+    "m_col = {}\n",
+    "m_xx = {}\n",
+    "dict1 = {}\n",
+    "list1 = []\n",
+    "for x in mycol.find({\"code\":{'$exists': 'true'}},{\"_id\": 0, \"code\": 1, \"name\": 1}):\n",
+    "    m_col[x['code']] = x['name']\n",
+    "\n",
+    "with open('data/2022.json','r') as fl:\n",
+    "    m_xx = json.load(fl)\n",
+    "for k, v in m_xx.items():\n",
+    "    #code = v[1][:4]\n",
+    "    dict1[v[1][:4]]= v[1][4:]\n",
+    "for code in dict1.keys():\n",
+    "    if code not in m_col.keys():\n",
+    "        #print(dict1[code])\n",
+    "        \n",
+    "        if dict1[code] not in m_col.values():\n",
+    "            list1.append(code)\n",
+    "print(list1)\n",
+    "for x in mycol.find({\"id_code\":{'$exists': 'true'}},{\"_id\": 0, \"id_code\": 1, \"name\": 1}):\n",
+    "    m_col[x['id_code']] = x['name']\n",
+    "for code in list1:\n",
+    "    if dict1[code] in m_col.values():\n",
+    "        myquery = {'name':dict1[code]}\n",
+    "        m_new = {\"$set\":{'code':code}}\n",
+    "        mycol.update_one(myquery,m_new)\n",
+    "        print(dict1[code])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 汇总2022年学校录取情况"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import pymysql\n",
+    "import pymongo\n",
+    "\n",
+    "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
+    "mydb = myclient[\"gaokao\"]\n",
+    "mycol = mydb[\"college_2021\"]\n",
+    "m_xx = {}\n",
+    "m_data = {}\n",
+    "m_mongo = {}\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"root\",password = \"songyi\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "sql = 'SELECT college,SUM(plan),min(num_min),max(RANK_min) FROM admission_2022 GROUP BY college'\n",
+    "cursor.execute(sql)\n",
+    "results = cursor.fetchall()\n",
+    "i = 1\n",
+    "for result in results:\n",
+    "    #m_xx.clear()\n",
+    "    m_code = result[0]\n",
+    "    m_nian ='2022'\n",
+    "    m_lb = 'z'\n",
+    "    m_xx.setdefault(m_code,{})\n",
+    "    m_xx[m_code].setdefault(m_nian,{})\n",
+    "    m_xx[m_code][m_nian].setdefault(m_lb,{})\n",
+    "    m_xx[m_code][m_nian][m_lb] ['name']= '综合'\n",
+    "    m_xx[m_code][m_nian][m_lb] ['dispense']= int(result[1])\n",
+    "    m_xx[m_code][m_nian][m_lb] ['num_min']= result[2]\n",
+    "    m_xx[m_code][m_nian][m_lb] ['rank_min']= result[3]    \n",
+    "    myquery = {'code':m_code}\n",
+    "    colleges = mycol.find(myquery,{ \"_id\": 0, \"admission\": 1 })\n",
+    "    for x in colleges:\n",
+    "        for k, v in x.items():\n",
+    "            for k1, v1 in v.items():\n",
+    "                m_xx[m_code][k1] = v1\n",
+    "for k,v in m_xx.items():\n",
+    "    #m_item ='admission.'+m_nian\n",
+    "    m_mongo.clear()    \n",
+    "    myquery = {'code':k}\n",
+    "    m_new = {\"$set\":{'admission':v}}\n",
+    "    mycol.update_one(myquery,m_new)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 整理2022年新增专业"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pymysql\n",
+    "import json\n",
+    "\n",
+    "l_data = []\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"root\",password = \"songyi\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "\n",
+    "with open('data/2022.json','r') as fl:\n",
+    "    m_xx = json.load(fl)\n",
+    "for k, v in m_xx.items():\n",
+    "    l_data.append([v[0][:2],v[0][2:],v[1][0:4],'2022'])\n",
+    "sql = \"insert into speciality (code,name,college,nian) values(%s,%s,%s,%s)\"\n",
+    "try:\n",
+    "    cursor.executemany(sql,l_data)\n",
+    "    db.commit()\n",
+    "    print(\"已添加！\")\n",
+    "except:\n",
+    "    # 如果发生错误则回滚\n",
+    "    print(\"error!\")\n",
+    "    db.rollback()   \n",
+    "db.close() "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2022年专业录取分数及位次"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-08-04T03:53:00.735786Z",
+     "iopub.status.busy": "2022-08-04T03:53:00.735257Z",
+     "iopub.status.idle": "2022-08-04T03:53:10.194351Z",
+     "shell.execute_reply": "2022-08-04T03:53:10.192776Z",
+     "shell.execute_reply.started": "2022-08-04T03:53:00.735737Z"
+    },
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ok\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pymysql\n",
+    "import pymongo\n",
+    "import decimal\n",
+    "\n",
+    "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
+    "mydb = myclient[\"gaokao\"]\n",
+    "mycol = mydb[\"college_2021\"]\n",
+    "mycol1 = mydb[\"admission_2022\"]\n",
+    "\n",
+    "m_col = {}\n",
+    "m_spe = {}\n",
+    "m_xx = {}\n",
+    "for x in mycol.find({\"code\":{'$exists': 'true'}},{\"_id\": 0, \"code\": 1, \"name\": 1}):\n",
+    "    m_col[x['code']] = x['name']\n",
+    "\n",
+    "\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"songyi\",password = \"yylzs\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "sql = 'SELECT a.code,a.college,a.name FROM speciality AS a WHERE a.nian=\"2022\"'\n",
+    "cursor.execute(sql)\n",
+    "results = cursor.fetchall()\n",
+    "for result in results:\n",
+    "    m_spe.setdefault(result[1],{})    \n",
+    "    m_spe[result[1]][result[0]] = result[2]\n",
+    "#print(m_spe)\n",
+    "sql = 'SELECT * FROM admission_2022 AS a where college not in (\"D628\",\"D440\",\"Y010\",\"D245\",\"D597\",\"D641\",\"D501\",\"D659\") ORDER BY a.rank_min'\n",
+    "#sql = 'SELECT * FROM admission_2022 AS a ORDER BY a.rank_min'\n",
+    "cursor.execute(sql)\n",
+    "results = cursor.fetchall()\n",
+    "i = 0\n",
+    "m_min = 0\n",
+    "ii = 0\n",
+    "for result in results:\n",
+    "    m_xx.clear()\n",
+    "    if result[4] == m_min:\n",
+    "        ii = ii\n",
+    "        i = i+1\n",
+    "    else:\n",
+    "        i = i+1\n",
+    "        ii = i\n",
+    "        m_min = result[6]\n",
+    "    \n",
+    "    m_xx['pos'] = ii\n",
+    "    m_xx['col_code'] = result[1]\n",
+    "    m_xx['col_name'] = m_col[result[1]]\n",
+    "    m_xx['spe_code'] = result[2]\n",
+    "    m_xx['spe_name'] = m_spe[result[1]][result[2]]\n",
+    "    m_xx['plan'] = result[3]\n",
+    "    m_xx['num_min'] = result[4]    \n",
+    "    m_xx['rank_min'] = result[5]\n",
+    "    m_xx['nian'] = '2022'    \n",
+    "    mycol1.insert_one(m_xx)\n",
+    "    #print(m_xx)\n",
+    "print('ok')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -1161,6 +1532,51 @@
     "db.close()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 导入2022年一分一段表"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import openpyxl\n",
+    "import pymysql\n",
+    "import json\n",
+    "\n",
+    "m_xx = []\n",
+    "db = pymysql.connect(host = \"localhost\",user = \"root\",password = \"songyi\",database = \"gaokao\" )\n",
+    "cursor = db.cursor()\n",
+    "wb = openpyxl.load_workbook('./data/2022一分一段表.xlsx')\n",
+    "sheet = wb.active\n",
+    "i = 1\n",
+    "for n in range(4,sheet.max_row):\n",
+    "        m_score = sheet.cell(n,1).value\n",
+    "        m_num = sheet.cell(n,2).value\n",
+    "        m_sum = sheet.cell(n,3).value\n",
+    "        m_max = m_sum - m_num + 1\n",
+    "        m_xx.append((m_score,m_num,m_max,m_sum,'z','2022'))\n",
+    "#print(m_xx)\n",
+    "sql = 'insert into fenduan(score,per_num,max_rank,min_rank,category,nian) values (%s,%s,%s,%s,%s,%s)'\n",
+    "try:\n",
+    "    cursor.executemany(sql,m_xx)\n",
+    "    db.commit()\n",
+    "    print(\"ok!\")\n",
+    "except:\n",
+    "    # 如果发生错误则回滚\n",
+    "    print(\"error!\")\n",
+    "    db.rollback()   \n",
+    "\n",
+    "db.close()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},