{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "19280f5c-8e34-4a64-8dfb-6353cbf597d2",
   "metadata": {},
   "source": [
    "# 体质检测数据处理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "112d80f4-607b-41f9-bb30-ac2eb8f52ee2",
   "metadata": {},
   "source": [
    "## 基础数据管理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7dfd50f-a614-497d-8f0a-fa1e4c89168a",
   "metadata": {},
   "source": [
    "### 体测项目标准导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cd73044-56a8-409b-a873-085feb63af17",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "tcbz ={\n",
    "    'HeightWeigh':'身高体重',\n",
    "    'StepExperiment':'台阶指数',\n",
    "    'Lung':'肺活量',\n",
    "    'Proneness':'坐位体前屈',\n",
    "    'PowerfullGrip':'握力',\n",
    "    'OneMinutePushUp':'一分钟仰卧起坐',\n",
    "    'PushUp':'俯卧撑',\n",
    "    'VerticalJump':'纵跳',\n",
    "    'ReactionTime':'选择反应时',\n",
    "    'FootStand':'单脚站立'\n",
    "}\n",
    "wb = openpyxl.load_workbook('data/体质检测标准.xlsx')\n",
    "sheet = wb.active\n",
    "# sheets = wb.sheetnames\n",
    "dict1 = {}\n",
    "dict3 = {}\n",
    "for k, v in tcbz.items():\n",
    "    dict3[v] = k\n",
    "sheet = wb.active\n",
    "data1 =list(sheet.values)\n",
    "del data1[0]\n",
    "for item in data1:\n",
    "    sex = item[0][6:]\n",
    "    if sex =='男':\n",
    "        age_sex = 'M'+item[0][:5]\n",
    "    else:\n",
    "        age_sex = 'F'+item[0][:5]\n",
    "    dict1.setdefault(age_sex,{})\n",
    "    if item[1] in dict3.keys():\n",
    "        xm = dict3[item[1]]\n",
    "    dict1[age_sex].setdefault(xm,[])\n",
    "    dict1[age_sex][xm].append(item[3]/item[4])\n",
    "dict2 = {}\n",
    "#print(dict1)\n",
    "for k, v in dict1.items():\n",
    "    i1 = int(k[1:3])\n",
    "    i2 = int(k[-2:])\n",
    "    m_sex = k[:1]\n",
    "    for i in range(i1,i2+1):\n",
    "        dict2[m_sex+str(i)] = k\n",
    "dict3 = {}\n",
    "dict3['person'] = dict2\n",
    "dict3['criteria'] = dict1\n",
    "filename = 'data/体质检测标准.json'\n",
    "with open(filename, 'w') as fl:\n",
    "    json.dump(dict3, fl, ensure_ascii=False)\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c36641d8-c54b-43d2-ad9d-ff4cb72deba9",
   "metadata": {},
   "source": [
    "### 身高标准导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ca52d7b-d77e-452f-98f6-95072a5a1934",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import openpyxl\n",
    "import json\n",
    "\n",
    "tcbz ={\n",
    "    'HeightWeigh':'身高体重',\n",
    "    'StepExperiment':'台阶指数',\n",
    "    'Lung':'肺活量',\n",
    "    'Proneness':'坐位体前屈',\n",
    "    'PowerfullGrip':'握力',\n",
    "    'OneMinutePushUp':'一分钟仰卧起坐',\n",
    "    'PushUp':'俯卧撑',\n",
    "    'VerticalJump':'纵跳',\n",
    "    'ReactionTime':'选择反应时',\n",
    "    'FootStand':'单脚站立'\n",
    "}\n",
    "wb = openpyxl.load_workbook('data/体质检测标准_BMI.xlsx')\n",
    "sheet = wb.active\n",
    "# sheets = wb.sheetnames\n",
    "dict1 = {}\n",
    "dict3 = {}\n",
    "for k, v in tcbz.items():\n",
    "    dict3[v] = k\n",
    "sheet = wb.active\n",
    "data1 =list(sheet.values)\n",
    "del data1[0]\n",
    "for item in data1:\n",
    "    min_age = int(item[1]/12)\n",
    "    max_age = int((item[2]+1)/12) - 1\n",
    "    sex = item[0]\n",
    "    height = int(item[3])\n",
    "    if sex ==0:\n",
    "        age_sex = 'M'+str(min_age)+'~'+str(max_age)\n",
    "    else:\n",
    "        age_sex = 'F'+str(min_age)+'~'+str(max_age)\n",
    "    dict1.setdefault(age_sex,{})\n",
    "    \n",
    "    dict1[age_sex].setdefault(height,[])\n",
    "    dict1[age_sex][height].append(item[5]/1000)\n",
    "dict2 = {}\n",
    "#print(dict1)\n",
    "for k, v in dict1.items():\n",
    "    i1 = int(k[1:3])\n",
    "    i2 = int(k[-2:])\n",
    "    m_sex = k[:1]\n",
    "    for i in range(i1,i2+1):\n",
    "        dict2[m_sex+str(i)] = k\n",
    "dict3 = {}\n",
    "dict3['person'] = dict2\n",
    "dict3['criteria'] = dict1\n",
    "filename = 'data/体质检测标准_BMI.json'\n",
    "with open(filename, 'w') as fl:\n",
    "    json.dump(dict3, fl, ensure_ascii=False)\n",
    "print('ok')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f5708d-c2d0-4470-b2f4-b9face431865",
   "metadata": {},
   "source": [
    "### 计算分数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f32b266a-7e46-4703-ab61-7cbbc81b5ab1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import time\n",
    "import csv\n",
    "\n",
    "filename = 'data/体质检测标准.json'\n",
    "item = {}\n",
    "unit = {}\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "person = dict1['person']\n",
    "criteria = dict1['criteria']\n",
    "data = {'name':'张三','sex':'M','age':59,'item':'PowerfullGrip','result':51.0}\n",
    "info = data['sex']+str(data['age'])\n",
    "bz = person[info]\n",
    "mx = criteria[bz][data['item']]\n",
    "result = data['result']\n",
    "score = -1\n",
    "print(mx)\n",
    "for bz1 in mx:\n",
    "    if result < bz1:\n",
    "        print(bz1)\n",
    "        score = mx.index(bz1,0)\n",
    "        break\n",
    "    else:\n",
    "        score = 5\n",
    "#if score == -1:\n",
    " #   score = 5\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "755f8b66-c71c-4138-bd12-dff24e85e36a",
   "metadata": {},
   "source": [
    "### 计算BMI分数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "b32fbbdd-eb0a-4f0d-8901-e39a727c3ff8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-30T01:48:23.869481Z",
     "iopub.status.busy": "2023-04-30T01:48:23.868619Z",
     "iopub.status.idle": "2023-04-30T01:48:23.882339Z",
     "shell.execute_reply": "2023-04-30T01:48:23.881272Z",
     "shell.execute_reply.started": "2023-04-30T01:48:23.869438Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M50~59\n",
      "177.0,81.1\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import time\n",
    "import csv\n",
    "\n",
    "filename = 'data/体质检测标准_BMI.json'\n",
    "item = {}\n",
    "unit = {}\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "person = dict1['person']\n",
    "criteria = dict1['criteria']\n",
    "data = {'name':'张三','sex':'M','age':59,'item':'HeightWeight','result':'177.0,81.1'}\n",
    "info = data['sex']+str(data['age'])\n",
    "\n",
    "bz = person[info]\n",
    "print(bz)\n",
    "result = data['result']\n",
    "print(result)\n",
    "height = int(float(result.split(',')[0]))\n",
    "weight = float(result.split(',')[1])\n",
    "mx = criteria[bz][str(height)]\n",
    "if weight < mx[0]:\n",
    "    score = 1\n",
    "elif weight < mx[1]:\n",
    "    score = 3\n",
    "elif weight < mx[2]:\n",
    "    score = 5    \n",
    "elif weight <= mx[3]:\n",
    "    score = 3  \n",
    "elif weight > mx[3]:\n",
    "    score = 1\n",
    "print(score)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "732161bb-98f2-4861-ab66-7a374678bcd8",
   "metadata": {},
   "source": [
    "# 体质检测数据管理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb2db5e8-5dc6-4366-a39c-a3600ee5007c",
   "metadata": {},
   "source": [
    "## 数据导入Mycrm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc98d772-5841-41a3-ad8f-f7d1ff3b5fde",
   "metadata": {},
   "source": [
    "### 导入系统人员信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2cd93f45-6613-4a3f-97e4-5236068e1860",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import time\n",
    "import csv\n",
    "\n",
    "list1 = []\n",
    "filename = 'data/person_134.csv'\n",
    "with open(filename,'r',newline='') as csv_file:\n",
    "    fl = csv.reader(csv_file,delimiter=',')\n",
    "    header = next(fl)    \n",
    "    for line in fl:\n",
    "        #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
    "        list1.append(line)\n",
    "#print(list1)\n",
    "dict1 = {}\n",
    "for result in list1:\n",
    "    code = str(result[4])\n",
    "    if int(result[1]) == 0:\n",
    "        sex = '男'\n",
    "    else:\n",
    "        sex = '女'\n",
    "    \n",
    "    m_item = str(result[3])    \n",
    "    dict1.setdefault(code,{})    \n",
    "    dict1[code]['name'] = result[0]\n",
    "    dict1[code]['sex'] = sex\n",
    "    dict1[code]['birth'] = result[2]\n",
    "filename = 'data/天津石化人员清单.json'\n",
    "with open(filename,'w') as fl:\n",
    "    json.dump(dict1, fl, ensure_ascii=False) \n",
    "print(len(dict1))    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2eb50f19-c15f-4a36-87b7-cd02551d248d",
   "metadata": {},
   "source": [
    "### 导入测试项目item"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0eb37435-9c15-40ef-bd4c-2dffc026f59e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import psycopg2\n",
    "from psycopg2 import extras as ex\n",
    "\n",
    "filename = '../item.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "data_list = []\n",
    "for k, v in dict1.items():\n",
    "    data_list.append((int(k),v['name'])) \n",
    "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
    "cursor = conn.cursor()\n",
    "sql = 'insert into tianjin_item (id,name) values %s'\n",
    "ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
    "conn.commit()\n",
    "cursor.close()\n",
    "conn.close()\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ba97298-1e7e-4192-8d69-ea59f98e071a",
   "metadata": {},
   "source": [
    "### 导入一级部门"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9f7ed380-95f3-47d4-9eb5-74937af7811f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import psycopg2\n",
    "from psycopg2 import extras as ex\n",
    "\n",
    "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
    "cursor = conn.cursor()\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "unit = set()\n",
    "for k, v in dict1.items():\n",
    "    #if 'sub_unit' not in v.keys():\n",
    "    #    print(k,v['name'])\n",
    "    unit.add(v['unit'])\n",
    "print(unit)    \n",
    "i = 1\n",
    "dict2 = {}\n",
    "for item in unit:\n",
    "    dict2[item] = i\n",
    "    i+=1\n",
    "data_list = []\n",
    "for k,  v in dict2.items():\n",
    "    data_list.append((v,k)) \n",
    "    \n",
    "sql = 'insert into tianjin_unit (id,name) values %s'\n",
    "ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
    "conn.commit()\n",
    "cursor.close()\n",
    "conn.close()\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8a1fa7f-08ff-49bb-8052-9f86b1f2ac18",
   "metadata": {},
   "source": [
    "### 导入二级部门"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a13e81f2-467f-42c7-bb46-b547ef7bdd6c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import psycopg2\n",
    "from psycopg2 import extras as ex\n",
    "\n",
    "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
    "cursor = conn.cursor()\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "unit = set()\n",
    "for k, v in dict1.items():\n",
    "    #if 'sub_unit' not in v.keys():\n",
    "    #    print(k,v['name'])\n",
    "    unit.add(v['unit'])\n",
    "print(unit)    \n",
    "i = 1\n",
    "dict2 = {}\n",
    "for item in unit:\n",
    "    dict2[item] = i\n",
    "    i+=1\n",
    "data_list = []\n",
    "dict3 = {}\n",
    "for k,  v in dict1.items():\n",
    "    dict3.setdefault(v['unit'],set())\n",
    "    dict3[v['unit']].add(v['sub_unit'])\n",
    "i = 1    \n",
    "for k, v in dict3.items():\n",
    "    unit_id = dict2[k]\n",
    "    for item in v:\n",
    "        data_list.append((i,item,unit_id))\n",
    "        i+=1\n",
    "sql = 'insert into tianjin_sub_unit (id,name,unit_id) values %s'\n",
    "ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
    "conn.commit()\n",
    "cursor.close()\n",
    "conn.close()\n",
    "print('ok!')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53bf98fe-0ae9-402f-b8d8-495e8f31df3d",
   "metadata": {},
   "source": [
    "### 导入人员信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6af82fd2-b1d6-44b7-8b13-58883b58f8b0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import psycopg2\n",
    "from psycopg2 import extras as ex\n",
    "\n",
    "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
    "cursor = conn.cursor()\n",
    "filename = 'data/天津石化人员清单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    person = json.load(fl)\n",
    "    \n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "unit = set()\n",
    "for k, v in dict1.items():\n",
    "    #if 'sub_unit' not in v.keys():\n",
    "    #    print(k,v['name'])\n",
    "    unit.add(v['unit'])\n",
    "print(unit)    \n",
    "i = 1\n",
    "dict2 = {}\n",
    "for item in unit:\n",
    "    dict2[item] = i\n",
    "    i+=1\n",
    "data_list = []\n",
    "dict3 = {}\n",
    "dict4 = {}\n",
    "for k,  v in dict1.items():\n",
    "    dict3.setdefault(v['unit'],set())\n",
    "    dict3[v['unit']].add(v['sub_unit'])    \n",
    "i = 1    \n",
    "for k, v in dict3.items():\n",
    "    unit_id = dict2[k]\n",
    "    for item in v:\n",
    "        data_list.append((i,item,unit_id))\n",
    "        i+=1\n",
    "for item in data_list:\n",
    "    sub_id = item[0]\n",
    "    dict4[sub_id] = {'name':item[1],'unit':item[2]}\n",
    "dict5 = {}\n",
    "for k, v in dict1.items():\n",
    "    id_unit = dict2[v['unit']]\n",
    "    sub_name = v['sub_unit']\n",
    "    id_sub = 0\n",
    "    for k1, v1 in dict4.items():\n",
    "        if v1['name'] == sub_name and v1['unit'] == id_unit:\n",
    "            id_sub = int(k1)\n",
    "    if id_sub >0:\n",
    "        dict5[k] = {'unit':id_unit,'sub_unit':id_sub}\n",
    "    else:\n",
    "        print(k,'not fund')\n",
    "data_list = []\n",
    "for k, v in dict5.items():\n",
    "    id = int(k)\n",
    "    name = person[k]['name']\n",
    "    sex = person[k]['sex']\n",
    "    birth = person[k]['birth']\n",
    "    phone = ''\n",
    "    note = ''\n",
    "    unit = v['sub_unit']\n",
    "    data_list.append((id,name,sex,birth,unit))\n",
    "sql = 'insert into tianjin_person (id,name,sex,birth,unit_id) values %s'\n",
    "ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
    "conn.commit()\n",
    "cursor.close()\n",
    "conn.close()\n",
    "print('ok!')   \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd95a45a-c6df-47c3-9941-2d0579b2c5d9",
   "metadata": {},
   "source": [
    "### 导入测试成绩及得分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "360e61e9-7895-484b-a9d6-333bdefa1a86",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-04-29T14:29:07.198753Z",
     "iopub.status.busy": "2023-04-29T14:29:07.197888Z",
     "iopub.status.idle": "2023-04-29T14:29:08.464741Z",
     "shell.execute_reply": "2023-04-29T14:29:08.463607Z",
     "shell.execute_reply.started": "2023-04-29T14:29:07.198711Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ok!\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import psycopg2\n",
    "from psycopg2 import extras as ex\n",
    "\n",
    "filename = '../item.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "dict2 = {}\n",
    "for k, v in dict1.items():\n",
    "    dict2[v['name']] = int(k)\n",
    "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
    "cursor = conn.cursor()\n",
    "data_list = []\n",
    "filename = 'data/result_天津.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl) \n",
    "for k, v in dict1.items():\n",
    "    for item in v.keys():\n",
    "        if item in dict2.keys():\n",
    "            item_id = dict2[item]\n",
    "            if v[item]['得分'] == '\\\\N':\n",
    "                score = None\n",
    "            else:\n",
    "                score = int(v[item]['得分'])\n",
    "                \n",
    "            data_list.append((v[item]['成绩'],score,int(k),item_id))\n",
    "         \n",
    "sql = 'insert into tianjin_records (performance,score,avatar_id_id,item_id_id) values %s'\n",
    "ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
    "conn.commit()\n",
    "cursor.close()\n",
    "conn.close()\n",
    "print('ok!')           \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb747368-d3ac-4b29-ae4f-ce207d5fcd43",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "filename = 'data/天津石化人员名单.json'\n",
    "with open(filename,'r') as fl:\n",
    "    dict1 = json.load(fl)\n",
    "for k, v in dict1.items():\n",
    "    if 'num_id' not in v.keys():\n",
    "        print(k,v['name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51dc35a5-dc07-40a4-9ea7-375ca7f983c3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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