{ "cells": [ { "cell_type": "markdown", "id": "55644860-57e6-466b-b6e9-e6fdd807498d", "metadata": { "tags": [] }, "source": [ "# 员工体测" ] }, { "cell_type": "markdown", "id": "d4d999fe-4890-4a14-b1e8-52dbd6d42e73", "metadata": { "tags": [] }, "source": [ "## 导入人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "3154fc8c-0e91-4cda-ba75-666dc7bbb34d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/student_20140922长炼医院监测花名册.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 4).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 6).value\n", " if int(sheet.cell(n, 7).value) ==1:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " dict1['sex'] = sex\n", " birth = str(sheet.cell(n, 8).value).split()[0]\n", " dict1['birth'] = birth\n", " dict1['unit'] = sheet.cell(n, 3).value\n", " person[code] = dict1\n", "filename = 'data/长炼医院人员2024.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "31d36f3c-f046-40a9-bf90-ba139fdcce3a", "metadata": {}, "source": [ "## 新增人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "5cea2f5e-37fc-4857-8455-090a634a1c0a", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/长炼医院新增监测花名册（水务部）.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " person = json.load(fl) \n", "print(len(person))\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 4).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 6).value\n", " if int(sheet.cell(n, 7).value) ==1:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " dict1['sex'] = sex\n", " birth = str(sheet.cell(n, 8).value).split()[0]\n", " dict1['birth'] = birth\n", " dict1['unit'] = sheet.cell(n, 3).value\n", " person[code] = dict1\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')\n", "print(len(person))" ] }, { "cell_type": "markdown", "id": "56e4caa4-cf9d-4fdc-99c4-86f5e92afdfa", "metadata": {}, "source": [ "## 补充员工编号" ] }, { "cell_type": "code", "execution_count": null, "id": "0bdfe5e6-40e1-432d-85b4-ddb9e8d3dd90", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/长炼医院体测人员编号情况表.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " person = json.load(fl) \n", "print(len(person))\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = str(sheet.cell(n, 1).value)\n", " ygbh = str(sheet.cell(n, 6).value)\n", " if code in person.keys():\n", " person[code]['code'] = ygbh\n", " #print(code,person[code]['name'],ygbh)\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "1597f17a-1d9c-4d2c-9273-3afa8147c72e", "metadata": {}, "source": [ "## 单独新增人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "d6fde6c4-d696-4eb9-a73e-a7cc7018b62c", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " person = json.load(fl) \n", "code = '3297'\n", "name = '何治国'\n", "sex = '男'\n", "birth = '1982/02/15'\n", "unit = '长炼医院外二科'\n", "person[code] = {'name':name,'sex':sex,'birth':birth,'unit':unit}\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')\n", "print(len(person))" ] }, { "cell_type": "markdown", "id": "96d5b4bd-4198-4725-9005-070ac4e4f324", "metadata": {}, "source": [ "## 每日成绩导入" ] }, { "cell_type": "code", "execution_count": null, "id": "4b52477e-926a-44b5-b8a0-20bff98d101d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "rq = '20230830'\n", "filename = f'data/places_result_{rq}.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", "for result in list1:\n", " user = str(result[2])\n", " if user in dict1.keys(): \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex'] \n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " item_name = item[m_item]['name']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", "print(len(re_ta))\n", "\n", "filename = 'data/result_长炼医院.json'\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))\n" ] }, { "cell_type": "code", "execution_count": null, "id": "033cc564-4aa9-4e88-b38b-ec62a02b1661", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import datetime\n", "import csv\n", "from datetime import date\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "item['1']['en'] = 'lung'\n", "item['2']['en'] = 'grip'\n", "item['3']['en'] = 'flexion'\n", "item['4']['en'] = 'jump'\n", "item['5']['en'] = 'pushup'\n", "item['6']['en'] = 'balance'\n", "item['7']['en'] = 'reaction'\n", "item['8']['en'] = 'step'\n", "item['9']['en'] = 'situp'\n", "item['10']['en'] = 'height'\n", "item['11']['en'] = 'weight'\n", "\n", "\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20231202.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", "#f_item = ['lung','grip','flexion','jump','balance','reaction','step','situp']\n", "#m_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step']\n", "for result in list1:\n", " user = str(result[2])\n", " item_id = int(result[3])\n", " performance = int(result[4])\n", " if user in dict1.keys() and (item_id!=3 and performance>0):\n", " l_xm = []\n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex']\n", " if dict1[user]['sex'] == '男':\n", " l_xm = ['weight','height','lung','grip','flexion','jump','pushup','balance','reaction','step']\n", " else:\n", " l_xm = ['weight','height','lung','grip','flexion','jump','balance','reaction','step','situp']\n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " birth = date.fromisoformat(dict1[user]['birth'].replace('/','-'))\n", " #nian = int(birth[0].strip())\n", " #yue = int(birth[1].strip())\n", " #ri = int(birth[2].strip())\n", " #print(k,nian,yue,ri)\n", " item_name = item[m_item]['en'] \n", " if item_name in l_xm: \n", " days = (datetime.date(2023, 8, 29)-birth).days \n", " re_ta[user]['age'] = int(days/365)\n", " re_ta[user]['month'] = int(days/365*12)\n", "\n", "\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", "print(len(re_ta))\n", "filename = 'data/result_长炼医院.json'\n", "\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))" ] }, { "cell_type": "markdown", "id": "f220ffba-d172-4b6f-8238-c3a2d6c87ed4", "metadata": {}, "source": [ "## 每日成绩导出" ] }, { "cell_type": "code", "execution_count": null, "id": "2ffa583b-be51-40a8-bb55-de6a89d1a54a", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "#rq = '20230510'\n", "items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "title = ['编号','姓名','性别','单位','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "filename = f'data/result_长炼医院（{rq}).json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", " \n", "list1 = []\n", "for k, v in dict1.items():\n", " list2 = []\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['unit']) \n", " for item in items:\n", " if item in v.keys():\n", " list2.append(v[item]['成绩']) \n", " elif item =='name':\n", " list2.append(v[item])\n", " else:\n", " list2.append('') \n", " list1.append(list2)\n", "filename = f'data/长炼医院体测情况表({rq}).xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list1:\n", " sheet.append(row)\n", "wb.save(filename)" ] }, { "cell_type": "markdown", "id": "be9ba440-3978-4a26-96a8-a0ec4a4f307f", "metadata": {}, "source": [ "## 人员信息表导出" ] }, { "cell_type": "code", "execution_count": null, "id": "52e4d9cf-2ecd-4d96-9ab0-a71c507a32e0", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "for k, v in dict1.items():\n", " list2 = []\n", " list2 = [k,v['name'],v['sex'],v['birth'],v['unit']]\n", " list1.append(list2)\n", "filename = f'data/长炼医院体测情况表(20230829).xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "\n", "for row in list1:\n", " sheet.append(row)\n", "wb.save(filename)" ] }, { "cell_type": "markdown", "id": "f58f1da0-a558-4c92-ac09-341bc8a6055d", "metadata": {}, "source": [ "## 计算测试得分" ] }, { "cell_type": "code", "execution_count": null, "id": "3b10ab5b-a9e6-4b3b-b2ec-97a2de4af6cd", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict3 = json.load(fl) \n", "for k,v in dict3.items():\n", " item[k] = v\n", "item['1']['en'] = 'lung'\n", "item['2']['en'] = 'grip'\n", "item['3']['en'] = 'flexion'\n", "item['4']['en'] = 'jump'\n", "item['5']['en'] = 'pushup'\n", "item['6']['en'] = 'balance'\n", "item['7']['en'] = 'reaction'\n", "item['8']['en'] = 'step'\n", "item['9']['en'] = 'situp'\n", "item['10']['en'] = 'height'\n", "item['11']['en'] = 'weight'\n", "\n", "filename = 'data/体质检测标准 (1).json' \n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "\n", "\n", "def cal_score(data1):\n", " #data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46} \n", " person = dict1['person']\n", " criteria = dict1['criteria'] \n", " info = data1['sex']+str(data1['age'])\n", " bz = person[info]\n", " mx = criteria[bz][data1['item']]\n", " result = data1['result'] \n", " if data1['item'] == 'reaction':\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", " else:\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", " return(score)\n", "filename = 'data/体质检测标准_BMI.json'\n", "with open(filename,'r') as fl:\n", " dict4 = json.load(fl) \n", " \n", "def cal_bmi(data1):\n", " # data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n", " person = dict4['person']\n", " criteria = dict4['criteria']\n", " \n", " info = data1['sex']+str(data1['age'])\n", " bz = person[info]\n", " #print(bz)\n", " result = data1['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", " return score\n", " \n", " \n", "\n", "#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n", "filename = 'data/result_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl) \n", "for k, v in dict2.items():\n", " if v['sex'] == '男':\n", " sex = 'M'\n", " else:\n", " sex = 'F' \n", " if 'height' in v.keys() and 'weight' in v.keys():\n", " bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n", " data1 = {'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n", " dict2[k]['bmi'] = {}\n", " dict2[k]['bmi']['成绩'] = bmi_data\n", " dict2[k]['bmi']['score'] = cal_bmi(data1)\n", " for item_en in list_item:\n", " if item_en in v.keys(): \n", " data1 = {'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n", " dict2[k][item_en]['score'] = cal_score(data1)\n", " #print(k,v[item_en]['成绩'],cal_score(data1))\n", "\n", "filename = f'data/result_长炼医院.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "647c016d-640e-44ab-888d-09b80d5bb8b9", "metadata": {}, "source": [ "## 生成报告" ] }, { "cell_type": "code", "execution_count": null, "id": "bea5228f-0d65-4969-b00f-ea102ed12122", "metadata": { "tags": [] }, "outputs": [], "source": [ "import requests\n", "import json\n", "\n", "headers = {\n", " \"Content-Type\": \"application/json; charset=UTF-8\"\n", " }\n", "filename = 'data/result_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "fiie_path ='./469849/'\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n", "for k, v in dict1.items():\n", " list1 = []\n", " mydata = {}\n", " \n", " id = str(k).rjust(5,\"0\")\n", " mydata['path'] = fiie_path+id+'-'+ v['name']+'.pdf'\n", " mydata['title'] = '中石化长岭分公司'\n", " mydata['subtitle'] = v['unit']\n", " mydata['id'] = id\n", " mydata['name'] = v['name']\n", " if v['sex'] == '男':\n", " mydata['gender'] = 'male'\n", " else:\n", " mydata['gender'] = 'female'\n", " \n", " mydata['month'] = v['month']\n", " mydata['fits'] = {}\n", " for item in list_item:\n", " if item in v.keys():\n", " if item in ['lung','pushup','step','situp']:\n", " mark = v[item]['成绩'].split()[0].split('.')[0]\n", " else:\n", " mark = v[item]['成绩'].split()[0]\n", " mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n", " if len(mydata['fits']) >2:\n", " \n", " list1.append(mydata) \n", " x = requests.post('http://192.168.31.163:3003', data = json.dumps(list1), headers=headers)\n", " print(id,v['name'],x.text)\n", " x.close()\n", " #print(mydata)\n", " " ] }, { "cell_type": "markdown", "id": "effa061b-51f9-4074-b747-d7873217973a", "metadata": {}, "source": [ "## 生成报告数据" ] }, { "cell_type": "code", "execution_count": null, "id": "d403f2f4-ae6b-422f-9679-e7636bfec03e", "metadata": { "tags": [] }, "outputs": [], "source": [ "import requests\n", "import json\n", "\n", "headers = {\n", " \"Content-Type\": \"application/json; charset=UTF-8\"\n", " }\n", "filename = 'data/result_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "\n", "fiie_path ='./469849/'\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n", "for k, v in dict1.items(): \n", " mydata = {}\n", " id = str(k).rjust(5,\"0\")\n", " mydata['path'] = fiie_path+id+'-'+ v['name']+'.pdf'\n", " mydata['title'] = '中石化长岭分公司'\n", " mydata['subtitle'] = v['unit']\n", " mydata['id'] = id\n", " mydata['name'] = v['name']\n", " if v['sex'] == '男':\n", " mydata['gender'] = 'male'\n", " else:\n", " mydata['gender'] = 'female'\n", " \n", " mydata['month'] = v['month']\n", " mydata['fits'] = {}\n", " for item in list_item:\n", " if item in v.keys():\n", " if item in ['lung','pushup','step','situp']:\n", " mark = v[item]['成绩'].split()[0].split('.')[0]\n", " else:\n", " mark = v[item]['成绩'].split()[0]\n", " mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n", " if len(mydata['fits']) >2: \n", " list1.append(mydata) \n", " #x = requests.post('http://192.168.31.163:3003', data = json.dumps(list1), headers=headers)\n", " #print(id,v['name'],x.text)\n", " #x.close()\n", " #print(mydata)\n", "json_data = json.dumps(list1,ensure_ascii=False, indent=4) \n", "\n", "# 将 json 数据写入文件\n", "with open(\"data/长炼医院data.json\", \"w\",encoding = 'utf-8') as file:\n", " file.write(json_data) " ] }, { "cell_type": "markdown", "id": "1f74d57b-ef60-4a1e-8cb5-2dc4c96bdcca", "metadata": {}, "source": [ "## 核对成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "c1c3330d-cce6-4603-99ea-8401cfa11e05", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict3 = json.load(fl) \n", "for k,v in dict3.items():\n", " item[k] = v\n", "item['1']['en'] = 'lung'\n", "item['2']['en'] = 'grip'\n", "item['3']['en'] = 'flexion'\n", "item['4']['en'] = 'jump'\n", "item['5']['en'] = 'pushup'\n", "item['6']['en'] = 'balance'\n", "item['7']['en'] = 'reaction'\n", "item['8']['en'] = 'step'\n", "item['9']['en'] = 'situp'\n", "item['10']['en'] = 'height'\n", "item['11']['en'] = 'weight'\n", "\n", "re_ta = {}\n", "list1 = []\n", "item_list = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n", "filename = 'data/places_result_20230830.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", "for result in list1:\n", " user = str(result[2])\n", " \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " item_name = item[m_item]['en']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = result[5]\n", "\n", "filename = 'data/长炼医院data.json'\n", "with open(filename,'r') as fl:\n", " list1 = json.load(fl)\n", "for data in list1:\n", " code = str(int(data['id']))\n", " for k, v in data['fits'].items():\n", " if code in re_ta.keys():\n", " if k in item_list:\n", " print(code,k,v['score'],re_ta[code][k]['成绩'])\n", " if k == 'bmi':\n", " print(code,k,v['score'],re_ta[code]['weight']['成绩'])\n", " \n", " " ] }, { "cell_type": "markdown", "id": "83fa2c1f-5269-4dec-a6b5-43f809db808c", "metadata": {}, "source": [ "## 获取报告信息" ] }, { "cell_type": "code", "execution_count": null, "id": "f4aaab88-4a92-434c-98e5-2ef2f4c23707", "metadata": { "tags": [] }, "outputs": [], "source": [ "import os,sys,shutil\n", "import json\n", "import glob\n", "from pathlib import Path\n", "\n", "\n", "fi_path = 'file/469849'\n", "old = []\n", "dict2 = {}\n", "list1 = []\n", "\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", " \n", "fl = glob.glob(f'{fi_path}/*.pdf')\n", "for fn in fl:\n", " fi_name =Path(fn).stem.split('-')[0]\n", " code = int(fi_name)\n", " \n", " print(fi_name,dict1[str(code)]['name'],dict1[str(code)]['code'])\n" ] }, { "cell_type": "markdown", "id": "da49e006-b6ce-4834-8085-98fd80dd83b0", "metadata": {}, "source": [ "## 报告信息导入数据库" ] }, { "cell_type": "code", "execution_count": null, "id": "48b25b03-7203-4575-8a1e-2cf546f012a9", "metadata": { "tags": [] }, "outputs": [], "source": [ "import os,sys,shutil\n", "import json\n", "import glob\n", "from pathlib import Path\n", "import pymongo\n", "\n", "\n", "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n", "mydb = myclient[\"baogao\"]\n", "\n", "place_id = 469849\n", "fi_path = 'file/469849'\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", " \n", "fl = glob.glob(f'{fi_path}/*.pdf')\n", "list1 = []\n", "for fn in fl:\n", " dict2 = {}\n", " fi_name =Path(fn).stem.split('-')[0]\n", " code = int(fi_name)\n", " ygbh = dict1[str(code)]['code']\n", " dict2 = {'place_id':place_id,'code':ygbh,'fn':Path(fn).name}\n", " list1.append(dict2)\n", "mycol = mydb[\"pdf\"]\n", "x = mycol.insert_many(list1)\n", "print('ok') " ] }, { "cell_type": "markdown", "id": "b07923fd-94da-4b86-8902-523d3ebc3d1b", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "# 学生体测" ] }, { "cell_type": "markdown", "id": "6ba73ead-6715-46a6-b4a9-3a00b733b151", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "## 导入学生信息" ] }, { "cell_type": "code", "execution_count": null, "id": "c828b665-d178-42e4-a885-505045169102", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/小学生监测花名册.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 4).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 6).value\n", " if int(sheet.cell(n, 7).value) ==1:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " dict1['sex'] = sex\n", " birth = str(sheet.cell(n, 8).value).split()[0]\n", " dict1['birth'] = birth\n", " dict1['unit'] = sheet.cell(n, 3).value\n", " person[code] = dict1\n", "filename = 'data/长岭学生名单.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "9d64629c-f5ee-4c2b-a9a8-964259d06d36", "metadata": {}, "source": [ "## 每日成绩导入" ] }, { "cell_type": "code", "execution_count": null, "id": "3f1b2284-c39e-4dc2-bc0c-983fb8e3417f", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/长岭学生名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "rq = '20230914'\n", "filename = f'data/places_result_{rq}.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", "for result in list1:\n", " user = str(result[2])\n", " if user in dict1.keys(): \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex'] \n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " item_name = item[m_item]['name']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score}'\n", "print(len(re_ta))\n", "\n", "filename = 'data/result_长岭学生.json'\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))\n" ] }, { "cell_type": "markdown", "id": "33c3ecc6-4dee-4eb9-954e-00f3fbbc179d", "metadata": {}, "source": [ "## 每日成绩导入" ] }, { "cell_type": "code", "execution_count": null, "id": "9d5d379c-5b53-4716-b4ab-fa794c912853", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "#rq = '20230510'\n", "items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "title = ['编号','姓名','性别','单位','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "filename = f'data/result_长岭学生.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/长岭学生名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", " \n", "list1 = []\n", "for k, v in dict1.items():\n", " list2 = []\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['unit']) \n", " for item in items:\n", " if item in v.keys():\n", " list2.append(v[item]['成绩']) \n", " elif item =='name':\n", " list2.append(v[item])\n", " else:\n", " list2.append('') \n", " list1.append(list2)\n", "filename = f'data/长岭学生体测情况表.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list1:\n", " sheet.append(row)\n", "wb.save(filename)" ] }, { "cell_type": "markdown", "id": "707eec10-0650-4063-b25d-d833edf0f50b", "metadata": {}, "source": [ "## 汇总手工数据" ] }, { "cell_type": "code", "execution_count": null, "id": "6f4341d7-b836-4186-a4c6-370e9e207e0a", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = f'data/result_长岭学生.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/长岭学生名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "wb = openpyxl.load_workbook('data/潭溪小学学生体测数据.xlsx')\n", "sheet = wb.active\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,4).value is not None:\n", " code = int(sheet.cell(n, 4).value)\n", " if str(code) not in dict1.keys():\n", " dict1[str(code)] = dict2[str(code)]\n", " print(code)\n", " else:\n", " dict1[str(code)]['birth'] = dict2[str(code)]['birth']\n", " if sheet.cell(n,8).value is not None:\n", " dict1[str(code)].setdefault('50米跑',{})\n", " dict1[str(code)]['50米跑']['成绩'] = sheet.cell(n,8).value\n", " if sheet.cell(n,9).value is not None:\n", " dict1[str(code)].setdefault('一分钟跳绳',{})\n", " dict1[str(code)]['一分钟跳绳']['成绩'] = sheet.cell(n,9).value\n", " if sheet.cell(n,10).value is not None:\n", " dict1[str(code)].setdefault('一分钟仰卧起坐',{})\n", " dict1[str(code)]['一分钟仰卧起坐']['成绩'] = sheet.cell(n,10).value\n", " if sheet.cell(n,11).value is not None:\n", " dict1[str(code)].setdefault('50米x8往返跑',{})\n", " dict1[str(code)]['50米x8往返跑']['成绩'] = sheet.cell(n,11).value\n", "filename = f'data/result_长岭学生all.json'\n", "\n", "with open(filename, 'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False)\n", "print('ok') \n" ] }, { "cell_type": "markdown", "id": "de34017a-cbdb-4f76-adf3-453c698bdc3b", "metadata": {}, "source": [ "## 导出汇总数据" ] }, { "cell_type": "code", "execution_count": null, "id": "04e27e02-7a69-42a8-a21a-61151a8a1427", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = f'data/result_长岭学生all.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "items = ['身高','体重','肺活量','坐位体前屈','50米跑','一分钟跳绳','一分钟仰卧起坐','50米x8往返跑']\n", "for k, v in dict1.items(): \n", " list2 = []\n", " list2.append(str(k))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['unit']) \n", " for item in items:\n", " if item in v.keys():\n", " list2.append(v[item]['成绩']) \n", " else:\n", " list2.append('') \n", " list1.append(list2)\n", "filename = f'data/长岭学生体测情况表.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list1:\n", " sheet.append(row)\n", "wb.save(filename)" ] }, { "cell_type": "markdown", "id": "16473cee-7ca6-4092-a29a-ce0de31af247", "metadata": {}, "source": [ "## 汇总学生得分" ] }, { "cell_type": "code", "execution_count": null, "id": "38b01352-28cc-448f-8ca7-19d61cbeebc0", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'data/长岭学生名单.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "dict1 = {}\n", "wb = openpyxl.load_workbook('data/长岭学生体测成绩表.xlsx')\n", "sheet = wb.active\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = str(sheet.cell(n,1).value)\n", " dict1[code] = dict2[code]\n", " dict1[code]['grade'] = dict2[code]['unit'][:1]\n", " if sheet.cell(n,5).value is not None:\n", " dict1[code]['BMI'] = int(sheet.cell(n,5).value)\n", " if sheet.cell(n,6).value is not None:\n", " dict1[code]['肺活量'] = int(sheet.cell(n,6).value)\n", " if sheet.cell(n,7).value is not None:\n", " dict1[code]['坐位体前屈'] = int(sheet.cell(n,7).value)\n", " if sheet.cell(n,8).value is not None:\n", " dict1[code]['50米跑'] = int(sheet.cell(n,8).value)\n", " if sheet.cell(n,9).value is not None:\n", " dict1[code]['一分钟跳绳'] = int(sheet.cell(n,9).value)\n", " if sheet.cell(n,10).value is not None:\n", " dict1[code]['仰卧起坐'] = int(sheet.cell(n,10).value)\n", " if sheet.cell(n,11).value is not None:\n", " dict1[code]['往返跑'] = int(sheet.cell(n,11).value)\n", " \n", "filename = f'data/score_长岭学生.json'\n", "\n", "with open(filename, 'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False)\n", "print('ok') \n", " \n", " \n", " " ] }, { "cell_type": "markdown", "id": "48ed4623-63db-4abc-bf42-3873df1bff03", "metadata": {}, "source": [ "## 计算学生总分及平均分" ] }, { "cell_type": "code", "execution_count": null, "id": "ab7cc750-bff0-44ec-8652-21f8dc3100ef", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = f'data/score_长岭学生.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "items =['BMI','肺活量','坐位体前屈','50米跑','一分钟跳绳','仰卧起坐','往返跑']\n", "for k, v in dict1.items():\n", " i = 0\n", " t_score = 0\n", " for item in items:\n", " if item in v.keys():\n", " i+=1\n", " t_score = t_score + v[item]\n", " dict1[k]['总分'] = t_score\n", " dict1[k]['平均分'] =round(t_score/i,2)\n", " dict1[k]['项目数'] = i\n", "with open(filename, 'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False)\n", "print('ok') " ] }, { "cell_type": "markdown", "id": "0c903c43-8577-4075-b9bb-7fb37ec1a685", "metadata": {}, "source": [ "## 统计男女学生数据" ] }, { "cell_type": "code", "execution_count": null, "id": "5e15984f-0747-48ea-b71e-ffc8e30775c9", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = f'data/score_长岭学生.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "n = 0\n", "f = 0\n", "m = 0\n", "m_score = 0\n", "f_score = 0\n", "for k, v in dict1.items():\n", " if v['sex'] == '男':\n", " m+=1\n", " m_score = m_score + v['平均分']\n", " else:\n", " f+=1\n", " f_score = f_score + v['平均分']\n", "print('男性学生人数：',m)\n", "print('男性学生平均成绩：',m_score/m)\n", "print('女性学生人数：',f)\n", "print('女性学生平均成绩：',f_score/f)\n", "print('参加测试学生人数：',f+m)\n", "print('所有学生平均成绩：',(f_score+m_score)/(f+m)) \n", " " ] }, { "cell_type": "markdown", "id": "016c6e24-5f4e-4eee-9d01-de93c745fa0d", "metadata": {}, "source": [ "## 统计各年级学生数据" ] }, { "cell_type": "markdown", "id": "1de34752-0ed3-4601-9f55-88df263b3a62", "metadata": {}, "source": [ "### 按年级整理数据" ] }, { "cell_type": "code", "execution_count": null, "id": "bb71c8d2-e445-48c3-8673-84c965f6efe2", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = f'data/score_长岭学生.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "grade =['一','二','三','四','五','六']\n", "dict2 = {}\n", "items =['BMI','肺活量','坐位体前屈','50米跑','一分钟跳绳','仰卧起坐','往返跑']\n", "for k, v in dict1.items():\n", " sex = v['sex']\n", " dict2.setdefault(v['grade'],{})\n", " dict2[v['grade']].setdefault(sex,{})\n", " for item in v.keys():\n", " if item in items:\n", " dict2[v['grade']][sex].setdefault(item,[0.00,0,0])\n", " dict2[v['grade']][sex][item][0] = dict2[v['grade']][sex][item][0]+v[item]\n", " dict2[v['grade']][sex][item][1] = dict2[v['grade']][sex][item][1] + 1\n", " dict2[v['grade']][sex][item][2] = round(dict2[v['grade']][sex][item][0]/dict2[v['grade']][sex][item][1],2)\n", "filename = f'data/grade_长岭学生.json'\n", "\n", "with open(filename, 'w') as fl:\n", " json.dump(dict2, fl, ensure_ascii=False)\n", "print('ok') " ] }, { "cell_type": "code", "execution_count": null, "id": "35558059-3e86-4e74-8fde-794d1b2933c4", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = f'data/score_长岭学生.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "grade =['一','二','三','四','五','六']\n", "dict2 = {}\n", "items =['BMI','肺活量','坐位体前屈','50米跑','一分钟跳绳','仰卧起坐','往返跑']\n", "for k, v in dict1.items():\n", " sex = v['sex']\n", " dict2.setdefault(v['grade'],{}) \n", " for item in v.keys():\n", " if item in items:\n", " dict2[v['grade']].setdefault(item,[0.00,0,0])\n", " dict2[v['grade']][item][0] = dict2[v['grade']][item][0]+v[item]\n", " dict2[v['grade']][item][1] = dict2[v['grade']][item][1] + 1\n", " dict2[v['grade']][item][2] = round(dict2[v['grade']][item][0]/dict2[v['grade']][item][1],2)\n", "filename = f'data/grade_长岭学生(不区分性别).json'\n", "\n", "with open(filename, 'w') as fl:\n", " json.dump(dict2, fl, ensure_ascii=False)\n", "print('ok') " ] }, { "cell_type": "markdown", "id": "3e5e1db3-3f2a-42b4-afb4-5249067ef441", "metadata": {}, "source": [ "### 按年级计算平均分" ] }, { "cell_type": "code", "execution_count": null, "id": "68de3c86-53e5-470f-9afb-6781df3c1449", "metadata": { "tags": [] }, "outputs": [], "source": [ "filename = f'data/grade_长岭学生.json'\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "for k, v in dict1.items():\n", " print(f'{k}年级测试得分情况：')\n", " i = 0\n", " m_score = 0\n", " for k1,v1 in v['男'].items():\n", " i+=1\n", " m_score = m_score + v1[0]/v1[1]\n", " print(f'男生测试得分情况：',round(m_score/i,2))\n", " n = 0\n", " f_score = 0\n", " for k1,v1 in v['女'].items():\n", " n+=1\n", " f_score = f_score + v1[0]/v1[1]\n", " print(f'女生测试得分情况：',round(f_score/n,2))\n", " print(f'年级测试得分情况：',round((m_score+f_score)/(i+n),2))" ] }, { "cell_type": "markdown", "id": "da69c668-57e7-41bb-b4c6-5eac86d7e2b8", "metadata": {}, "source": [ "### 按年级计算项目平均分" ] }, { "cell_type": "code", "execution_count": null, "id": "eae0a7f3-ae42-499d-8b65-667b0b320dff", "metadata": {}, "outputs": [], "source": [ "filename = f'data/grade_长岭学生.json'\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "items =['BMI','肺活量','坐位体前屈','50米跑','一分钟跳绳','仰卧起坐','往返跑']\n", "for k, v in dict1.items():\n", " print(f'{k}年级测试得分情况：')\n", " f = 0\n", " m = 0\n", " f_score = 0\n", " m_score = 0\n", " for item in items:\n", " for k1,v1 in v['男'].items():\n", " if item in v1.keys():\n", " \n", " \n", " i+=1\n", " score = score + v1[0]/v1[1]" ] }, { "cell_type": "markdown", "id": "6cd42cb2-37a4-44e8-87cb-afd71b32e81f", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "# 教师体测" ] }, { "cell_type": "markdown", "id": "4ba29d0e-0af3-4c59-92cf-5c697ae20d16", "metadata": {}, "source": [ "## 导入教师信息" ] }, { "cell_type": "code", "execution_count": null, "id": "93cc6471-36b5-43ce-9128-1c06768b0d01", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/教职工监测花名册.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 4).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 6).value\n", " if int(sheet.cell(n, 7).value) ==1:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " dict1['sex'] = sex\n", " birth = str(sheet.cell(n, 8).value).split()[0]\n", " dict1['birth'] = birth\n", " dict1['unit'] = sheet.cell(n, 3).value\n", " person[code] = dict1\n", "filename = 'data/长岭教师名单.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "d2b61b63-2923-4fc9-ab0c-9ec8453760f2", "metadata": {}, "source": [ "## 每日成绩导入" ] }, { "cell_type": "code", "execution_count": null, "id": "41ed428a-30bc-4150-bf74-e25228e1ca67", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/长岭教师名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20231005.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", "for result in list1:\n", " user = str(result[2])\n", " if user in dict1.keys(): \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex'] \n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " re_ta[user]['birth'] = dict1[user]['birth']\n", " item_name = item[m_item]['name']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", "print(len(re_ta))\n", "filename = 'data/result_长岭教师.json'\n", "\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))\n" ] }, { "cell_type": "markdown", "id": "839bd6f9-f262-4640-99ea-2391caf63830", "metadata": {}, "source": [ "## 计算人员年龄" ] }, { "cell_type": "code", "execution_count": null, "id": "5e49f274-09d9-4eb6-ad4a-b70d217b6aa0", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import datetime\n", "\n", "filename = 'data/result_长岭教师.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "for k, v in dict1.items():\n", " #print(k,v)\n", " if '.' in v['birth']:\n", " birth = v['birth'].split()[0].split('.')\n", " else:\n", " birth = v['birth'].split()[0].split('/')\n", " \n", " nian = int(birth[0].strip())\n", " yue = int(birth[1].strip())\n", " ri = int(birth[2].strip())\n", " #print(k,nian,yue,ri)\n", " days = (datetime.date(2023, 9, 11)-datetime.date(nian,yue,ri)).days\n", " v['age'] = int(days/365)\n", "filename = 'data/result_长岭教师.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print('ok') " ] }, { "cell_type": "markdown", "id": "8d0834c0-0cb7-4172-b01f-3ef8227e3d72", "metadata": {}, "source": [ "## 计算测试得分" ] }, { "cell_type": "code", "execution_count": null, "id": "67fbefc0-a899-460d-a8c9-7d0633a33d7a", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict3 = json.load(fl) \n", "for k,v in dict3.items():\n", " item[k] = v\n", "item['1']['en'] = 'lung'\n", "item['2']['en'] = 'grip'\n", "item['3']['en'] = 'flexion'\n", "item['4']['en'] = 'jump'\n", "item['5']['en'] = 'pushup'\n", "item['6']['en'] = 'balance'\n", "item['7']['en'] = 'reaction'\n", "item['8']['en'] = 'step'\n", "item['9']['en'] = 'situp'\n", "item['10']['en'] = 'height'\n", "item['11']['en'] = 'weight'\n", "\n", "filename = 'data/体质检测标准 (1).json' \n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "\n", "\n", "def cal_score(data1):\n", " #data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46} \n", " person = dict1['person']\n", " criteria = dict1['criteria'] \n", " info = data1['sex']+str(data1['age'])\n", " bz = person[info]\n", " mx = criteria[bz][data1['item']]\n", " result = data1['result'] \n", " if data1['item'] == 'reaction':\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", " else:\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", " return(score)\n", "filename = 'data/体质检测标准_BMI.json'\n", "with open(filename,'r') as fl:\n", " dict4 = json.load(fl) \n", " \n", "def cal_bmi(data1):\n", " # data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n", " person = dict4['person']\n", " criteria = dict4['criteria']\n", " \n", " info = data1['sex']+str(data1['age'])\n", " bz = person[info]\n", " #print(bz)\n", " result = data1['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", " return score\n", " \n", " \n", "\n", "#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n", "filename = 'data/result_长岭教师.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl) \n", "for k, v in dict2.items():\n", " if v['sex'] == '男':\n", " sex = 'M'\n", " else:\n", " sex = 'F' \n", " if 'height' in v.keys() and 'weight' in v.keys():\n", " bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n", " data1 = {'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n", " dict2[k]['bmi'] = {}\n", " dict2[k]['bmi']['成绩'] = bmi_data\n", " dict2[k]['bmi']['score'] = cal_bmi(data1)\n", " for item_en in list_item:\n", " if item_en in v.keys(): \n", " data1 = {'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n", " dict2[k][item_en]['score'] = cal_score(data1)\n", " #print(k,v[item_en]['成绩'],cal_score(data1))\n", "\n", "filename = f'data/result_长岭教师.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print('ok!') " ] }, { "cell_type": "code", "execution_count": null, "id": "fc43f558-a22d-4872-bca1-f87066ab4fe4", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "a26bb4e2-106f-4e72-b102-7141fdf23f85", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n", "filename = 'data/result_长岭教师.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " print(k)\n", " score = 0\n", " i = 0 \n", " for k1,v1 in v.items(): \n", " if k1 in list_item:\n", " score = score + int(v1['score'])\n", " i+=1\n", " dict1[k]['score'] = round(score/i,2) \n", "\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print('ok')" ] }, { "cell_type": "markdown", "id": "970ac26e-6db4-4457-aa85-d672373c9479", "metadata": {}, "source": [ "## 计算平均成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "861a91f2-6256-4713-8028-6d6aae3b917d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = f'data/result_长岭教师.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "i = 1\n", "m = 0\n", "f = 0\n", "score = 0\n", "t_score = 0\n", "for k,v in dict1.items():\n", " if v['sex'] == '男':\n", " m = m +1\n", " score = score+v['score']\n", "print(f'平均成绩：{round(score/m,4)}分，男性：{m}人')\n", "t_score = t_score + score\n", "score = 0\n", "for k,v in dict1.items():\n", " if v['sex'] == '女':\n", " f = f +1\n", " score = score+v['score']\n", "print(f'平均成绩：{round(score/f,4)}分，女性：{f}人')\n", "t_score = t_score + score\n", "print(f'平均成绩：{round(t_score/38,4)}分，总体：38人')" ] }, { "cell_type": "markdown", "id": "db9ba2e8-a7b0-472f-84c2-84872643a385", "metadata": {}, "source": [ "## 计算各项目平均成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "5f112c32-5402-4fe9-b737-2c9c65ba0d49", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "filename = f'data/result_长岭教师.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "i = 1\n", "m = 0\n", "f = 0\n", "score = 0\n", "t_score = 0\n", "list_item = ['lung','flexion','reaction','bmi']\n", "for item in list_item:\n", " m = 0\n", " f = 0\n", " score = 0\n", " t_score = 0\n", " for k,v in dict1.items():\n", " if v['sex'] == '男' and item in v.keys():\n", " m = m +1\n", " score = score+v['score']\n", " print(f'{item}平均成绩：{round(score/m,4)}分，男性：{m}人')\n", " t_score = t_score + score\n", " score = 0\n", " for k,v in dict1.items():\n", " if v['sex'] == '女' and item in v.keys():\n", " f = f +1\n", " score = score+v['score']\n", " print(f'{item}平均成绩：{round(score/f,4)}分，女性：{f}人')\n", " t_score = t_score + score\n", " print(f'{item}平均成绩：{round(t_score/(f+m),4)}分，总体：{f+m}人')" ] }, { "cell_type": "markdown", "id": "78942564-c286-4f4e-8d89-515a2b4b4c86", "metadata": { "jp-MarkdownHeadingCollapsed": true }, "source": [ "# 员工数据分析" ] }, { "cell_type": "markdown", "id": "ee99edaa-700f-4eb3-bcf9-1366d4fefd76", "metadata": {}, "source": [ "## 获取人员测试成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "48f91581-2556-40d0-b0fe-ee98edb3983f", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import datetime\n", "import csv\n", "from datetime import date\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "item['1']['en'] = 'lung'\n", "item['2']['en'] = 'grip'\n", "item['3']['en'] = 'flexion'\n", "item['4']['en'] = 'jump'\n", "item['5']['en'] = 'pushup'\n", "item['6']['en'] = 'balance'\n", "item['7']['en'] = 'reaction'\n", "item['8']['en'] = 'step'\n", "item['9']['en'] = 'situp'\n", "item['10']['en'] = 'height'\n", "item['11']['en'] = 'weight'\n", "\n", "\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/长炼医院人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20231202.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", "#f_item = ['lung','grip','flexion','jump','balance','reaction','step','situp']\n", "#m_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step']\n", "for result in list1:\n", " user = str(result[2])\n", " item_id = int(result[3])\n", " performance = int(result[4])\n", " rq = date.fromisoformat(result[6].replace('/','-'))\n", " if user in dict1.keys() and (item_id!=3 or performance>0):\n", " l_xm = []\n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex']\n", " if dict1[user]['sex'] == '男':\n", " l_xm = ['weight','height','lung','grip','flexion','jump','pushup','balance','reaction','step']\n", " else:\n", " l_xm = ['weight','height','lung','grip','flexion','jump','balance','reaction','step','situp']\n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " birth = date.fromisoformat(dict1[user]['birth'].replace('/','-'))\n", " #nian = int(birth[0].strip())\n", " #yue = int(birth[1].strip())\n", " #ri = int(birth[2].strip())\n", " #print(k,nian,yue,ri)\n", " item_name = item[m_item]['en'] \n", " if item_name in l_xm: \n", " days = (rq-birth).days \n", " re_ta[user]['age'] = int(days/365)\n", " re_ta[user]['month'] = int(days/365*12)\n", " re_ta[user]['rq'] = result[6]\n", "\n", "\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", "print(len(re_ta))\n", "filename = 'data/result_长炼医院.json'\n", "\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))" ] }, { "cell_type": "markdown", "id": "35f5c65e-0efb-4870-9981-6f7a0b910ac2", "metadata": {}, "source": [ "## 计算项目成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "160841a0-a092-4457-8ce0-fe39910c5da5", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict3 = json.load(fl) \n", "for k,v in dict3.items():\n", " item[k] = v\n", "item['1']['en'] = 'lung'\n", "item['2']['en'] = 'grip'\n", "item['3']['en'] = 'flexion'\n", "item['4']['en'] = 'jump'\n", "item['5']['en'] = 'pushup'\n", "item['6']['en'] = 'balance'\n", "item['7']['en'] = 'reaction'\n", "item['8']['en'] = 'step'\n", "item['9']['en'] = 'situp'\n", "item['10']['en'] = 'height'\n", "item['11']['en'] = 'weight'\n", "\n", "filename = 'data/体质检测标准 (1).json' \n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "\n", "\n", "def cal_score(data1):\n", " #data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46} \n", " person = dict1['person']\n", " criteria = dict1['criteria']\n", " if data1['age'] >59:\n", " data1['age'] = 59\n", " if data1['age'] <20:\n", " data1['age'] = 20\n", " info = data1['sex']+str(data1['age'])\n", " bz = person[info]\n", " mx = criteria[bz][data1['item']]\n", " result = data1['result'] \n", " if data1['item'] == 'reaction':\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", " else:\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", " return(score)\n", "filename = 'data/体质检测标准_BMI.json'\n", "with open(filename,'r') as fl:\n", " dict4 = json.load(fl) \n", " \n", "def cal_bmi(data1):\n", " # data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n", " person = dict4['person']\n", " criteria = dict4['criteria']\n", " if data1['age'] > 59:\n", " data1['age'] = 59\n", " if data1['age'] <20:\n", " data1['age'] = 20\n", " info = data1['sex']+str(data1['age'])\n", " bz = person[info]\n", " #print(bz)\n", " result = data1['result']\n", " #print(data1['code'],result)\n", " height = int(float(result.split(',')[0]))\n", " weight = float(result.split(',')[1])\n", " if str(height) not in criteria[bz]:\n", " score = 1\n", " else: \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", " return score \n", " \n", "\n", "#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n", "filename = 'data/result_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl) \n", "for k, v in dict2.items():\n", " #print(k)\n", " if v['sex'] == '男':\n", " sex = 'M'\n", " else:\n", " sex = 'F' \n", " if 'height' in v.keys() and 'weight' in v.keys():\n", " bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n", " data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n", " dict2[k]['bmi'] = {}\n", " dict2[k]['bmi']['成绩'] = bmi_data\n", " dict2[k]['bmi']['score'] = cal_bmi(data1)\n", " for item_en in list_item:\n", " if item_en in v.keys(): \n", " data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n", " dict2[k][item_en]['score'] = cal_score(data1)\n", " #print(k,v[item_en]['成绩'],cal_score(data1))\n", "\n", "filename = f'data/result_长炼医院.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "bdded0c9-7616-4cf1-9788-8bb008944bee", "metadata": {}, "source": [ "## 清理报告数据" ] }, { "cell_type": "code", "execution_count": null, "id": "ed4c5a19-1c9e-4c63-8fdd-30b36ecc047a", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "\n", "filename = 'data/result_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", " \n", "#items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "items = {}\n", "items['lung'] = '肺活量'\n", "items['grip'] ='握力'\n", "items['flexion'] ='坐位体前屈'\n", "items['jump'] ='纵跳'\n", "items['pushup'] ='俯卧撑'\n", "items['balance'] ='单脚站立'\n", "items['reaction'] ='选择反应时'\n", "items['step'] ='台阶指数'\n", "items['situp'] ='一分钟仰卧起坐'\n", "items['bmi'] ='BMI'\n", "\n", "\n", "list1 = []\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n", "i=1\n", "list2 = []\n", "dict2 = {}\n", "for k, v in dict1.items():\n", " list1 = []\n", " mydata = {}\n", " \n", " id = str(k).rjust(8,\"0\")\n", " mydata['unit'] = v['unit']\n", " mydata['name'] = v['name']\n", " mydata['sex'] = v['sex']\n", " mydata['month'] = v['month']\n", " age = int(v['month']/12)\n", " if age <20:\n", " mydata['age'] = 20\n", " else:\n", " mydata['age'] = int(v['month']/12)\n", " \n", " mydata['fits'] = {}\n", " score = 0\n", " for item in list_item:\n", " if item in v.keys():\n", " if item in ['lung','pushup','step','situp']:\n", " mark = v[item]['成绩'].split()[0].split('.')[0]\n", " else:\n", " mark = v[item]['成绩'].split()[0]\n", " mydata['fits'][items[item]] = {'mark':mark,'score':v[item]['score']}\n", " score = score + v[item]['score']\n", " if len(mydata['fits'])>0:\n", " mydata['score'] = round(score/len(mydata['fits']),2)\n", " if len(mydata['fits']) >2:\n", " dict2[str(k)] = mydata\n", "print(len(dict2))\n", "filename = f'data/data_长炼医院.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "a802ad72-494f-4db5-93a0-9e2cd88a65fe", "metadata": {}, "source": [ "## 计算测试等级" ] }, { "cell_type": "code", "execution_count": null, "id": "14788ff3-0f3d-4ba2-b162-1f0663389a9d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "\n", "filename = 'data/data_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "dict2['不合格'] = [0,255]\n", "dict2['合格'] = [256,332]\n", "dict2['良好'] = [333,367]\n", "dict2['优秀'] = [368,500]\n", "\n", "for k1, v1 in dict2.items():\n", " di = v1[0]\n", " gao = v1[1]\n", " i = 0 \n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if int(v['score']*100) in range(di,gao+1):\n", " dict1[k]['level'] = k1\n", " i+=1\n", " if v['sex'] == '男':\n", " m = m +1\n", " else:\n", " f = f+1\n", " print(f'{di}~{gao}分人数：{i}人,男性：{m}人,女性:{f}人')\n", "print(len(dict1))" ] }, { "cell_type": "markdown", "id": "ca9b178d-bcdc-40ff-afa4-15718f10a24a", "metadata": {}, "source": [ "## 根据年龄汇总人员信息及成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "257917a2-5b29-4cd9-a798-4fd8e75ffe9c", "metadata": { "tags": [] }, "outputs": [], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " i = 1\n", " score = 0\n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1):\n", " score = score+v['score']\n", " i+=1\n", " if v['sex'] == '男':\n", " m = m +1\n", " \n", " print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i-1}人,男性：{m}人')" ] }, { "cell_type": "markdown", "id": "6b0651da-ade9-4cb4-b1c1-12b9e4dc267a", "metadata": {}, "source": [ "# 员工体测2024年" ] }, { "cell_type": "code", "execution_count": null, "id": "0b877c2a-7fb3-4b34-81ab-58b9a09c4890", "metadata": {}, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/湖南石化青年体质检测.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(3, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 4).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 6).value\n", " if int(sheet.cell(n, 7).value) ==1:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " dict1['sex'] = sex\n", " birth = str(sheet.cell(n, 8).value).split()[0]\n", " dict1['birth'] = birth\n", " dict1['unit'] = sheet.cell(n, 3).value\n", " person[code] = dict1\n", "filename = 'data/湖南石化青年体质检测.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "code", "execution_count": 8, "id": "610b20f3-9fd8-46fc-b8ee-d48c4c854289", "metadata": { "execution": { "iopub.execute_input": "2024-07-08T07:09:49.763833Z", "iopub.status.busy": "2024-07-08T07:09:49.763076Z", "iopub.status.idle": "2024-07-08T07:09:49.792041Z", "shell.execute_reply": "2024-07-08T07:09:49.791388Z", "shell.execute_reply.started": "2024-07-08T07:09:49.763760Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok\n" ] } ], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/湖南石化青年体质检测.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(3, sheet.max_row+1):\n", " if sheet.cell(n,1).value is not None:\n", " code = int(sheet.cell(n, 3).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 4).value\n", " dict1['sex'] = sheet.cell(n, 5).value\n", " birth = str(sheet.cell(n, 8).value).split()[0]\n", " dict1['birth'] = birth\n", " dict1['unit'] = sheet.cell(n, 2).value\n", " person[code] = dict1\n", "filename = 'data/湖南石化青年体质检测.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "b056832e-049c-40f4-b7e7-adac6976bf77", "metadata": {}, "source": [ "## 获取人员测试成绩" ] }, { "cell_type": "code", "execution_count": 3, "id": "1e2d586e-6ff5-4fd1-a909-278d23e54561", "metadata": { "execution": { "iopub.execute_input": "2024-09-29T05:14:10.446230Z", "iopub.status.busy": "2024-09-29T05:14:10.445350Z", "iopub.status.idle": "2024-09-29T05:14:10.477950Z", "shell.execute_reply": "2024-09-29T05:14:10.477374Z", "shell.execute_reply.started": "2024-09-29T05:14:10.446151Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "212\n", "212\n" ] } ], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/长炼医院人员2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20240929.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", "for result in list1:\n", " user = str(result[2])\n", " if user in dict1.keys(): \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex'] \n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " item_name = item[m_item]['name']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", "print(len(re_ta))\n", "filename = 'data/result_长炼医院人员2024.json'\n", "\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl, ensure_ascii=False) \n", "print(len(re_ta))" ] }, { "cell_type": "markdown", "id": "8af6a13c-3be4-44ff-a937-ee5061454484", "metadata": {}, "source": [ "## 导出测试人员信息" ] }, { "cell_type": "code", "execution_count": 4, "id": "64c6e1e3-801c-4573-b78f-5a9e842597a9", "metadata": { "execution": { "iopub.execute_input": "2024-09-29T05:14:43.182012Z", "iopub.status.busy": "2024-09-29T05:14:43.181450Z", "iopub.status.idle": "2024-09-29T05:14:43.242249Z", "shell.execute_reply": "2024-09-29T05:14:43.241683Z", "shell.execute_reply.started": "2024-09-29T05:14:43.181959Z" } }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "title = ['编号','姓名','性别','单位','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "\n", "filename = 'data/result_长炼医院人员2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/长炼医院人员2024.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", " \n", "list1 = []\n", "for k, v in dict1.items():\n", " if k in dict2.keys():\n", " list2 = []\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['unit'])\n", " for item in items:\n", " if item in v.keys():\n", " list2.append(v[item]['成绩']) \n", " elif item =='name':\n", " list2.append(v[item])\n", " else:\n", " list2.append('') \n", " list1.append(list2)\n", "filename = 'data/长炼医院人员检测情况表（20240720）.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list1:\n", " sheet.append(row)\n", " \n", "wb.save(filename)" ] }, { "cell_type": "code", "execution_count": null, "id": "f2345606-fe1b-49d4-b99b-f94aeec593eb", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }