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jupyter/体测单位/长炼医院.ipynb
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512song 82372feb99 20241211
2024-12-11 18:57:54 +08:00

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{
"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": 24,
"id": "610b20f3-9fd8-46fc-b8ee-d48c4c854289",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-09T09:22:38.802119Z",
"iopub.status.busy": "2024-12-09T09:22:38.801372Z",
"iopub.status.idle": "2024-12-09T09:22:38.835995Z",
"shell.execute_reply": "2024-12-09T09:22:38.835477Z",
"shell.execute_reply.started": "2024-12-09T09:22:38.802047Z"
}
},
"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",
"del person[1]\n",
"del person[2]\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": "4451ac02-b5c4-4e6c-88cf-9dd6f2067763",
"metadata": {},
"source": [
"## 汇总2023、2024人员"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a6dc8ae7-5a51-4eb1-954e-19c17b6062cd",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-05T01:26:00.236419Z",
"iopub.status.busy": "2024-12-05T01:26:00.235845Z",
"iopub.status.idle": "2024-12-05T01:26:00.282366Z",
"shell.execute_reply": "2024-12-05T01:26:00.281825Z",
"shell.execute_reply.started": "2024-12-05T01:26:00.236362Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"source": [
"import json\n",
"\n",
"filename = 'data/长炼医院人员2024.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \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",
"for k, v in dict2.items():\n",
" dict1[k] = v\n",
"filename = 'data/长炼医院人员2024（汇总）.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(dict1, 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": 26,
"id": "1e2d586e-6ff5-4fd1-a909-278d23e54561",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-09T09:26:07.189575Z",
"iopub.status.busy": "2024-12-09T09:26:07.187969Z",
"iopub.status.idle": "2024-12-09T09:26:07.219642Z",
"shell.execute_reply": "2024-12-09T09:26:07.219013Z",
"shell.execute_reply.started": "2024-12-09T09:26:07.189495Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"207\n",
"207\n"
]
}
],
"source": [
"import json\n",
"import time\n",
"import csv\n",
"\n",
"filename = '../item1.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_20241205-1.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": "code",
"execution_count": 7,
"id": "0cad0490-5199-4ca3-bf6f-a206829d702e",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-11T06:57:46.853287Z",
"iopub.status.busy": "2024-12-11T06:57:46.852519Z",
"iopub.status.idle": "2024-12-11T06:57:46.874391Z",
"shell.execute_reply": "2024-12-11T06:57:46.873811Z",
"shell.execute_reply.started": "2024-12-11T06:57:46.853199Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"78\n",
"78\n"
]
}
],
"source": [
"import json\n",
"import time\n",
"import csv\n",
"\n",
"filename = '../item1.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/湖南石化青年体质检测.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"filename = 'data/places_result_20241205-1.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（湖南青年）.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": "code",
"execution_count": 13,
"id": "dd681c34-dba9-434b-9cd3-ed12fefcce0f",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-11T07:10:57.109817Z",
"iopub.status.busy": "2024-12-11T07:10:57.109051Z",
"iopub.status.idle": "2024-12-11T07:10:57.134829Z",
"shell.execute_reply": "2024-12-11T07:10:57.134208Z",
"shell.execute_reply.started": "2024-12-11T07:10:57.109746Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"78\n",
"78\n"
]
}
],
"source": [
"import json\n",
"import datetime\n",
"import csv\n",
"from datetime import date\n",
"\n",
"filename = '../item1.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/湖南石化青年体质检测.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"\n",
"filename = 'data/places_result_20241205-1.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",
" rq = date.fromisoformat(result[6].replace('/','-'))\n",
" if user in dict1.keys():\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",
" #birth = date.fromisoformat(dict1[user]['birth'])\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_长炼医院人员2024（湖南青年）.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（湖南青年）"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "64c6e1e3-801c-4573-b78f-5a9e842597a9",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-09T09:23:41.690512Z",
"iopub.status.busy": "2024-12-09T09:23:41.689765Z",
"iopub.status.idle": "2024-12-09T09:23:41.726298Z",
"shell.execute_reply": "2024-12-09T09:23:41.725869Z",
"shell.execute_reply.started": "2024-12-09T09:23:41.690440Z"
}
},
"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/湖南石化青年体质检测.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（湖南青年）.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": "markdown",
"id": "02501bf0-0ba8-4143-b2ef-aeef767985d0",
"metadata": {},
"source": [
"## 导出测试人员信息（非湖南青年）"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "933f3eb1-8463-4782-ae45-8a1628abbb2b",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-09T09:29:03.983785Z",
"iopub.status.busy": "2024-12-09T09:29:03.983528Z",
"iopub.status.idle": "2024-12-09T09:29:04.043514Z",
"shell.execute_reply": "2024-12-09T09:29:04.042868Z",
"shell.execute_reply.started": "2024-12-09T09:29:03.983761Z"
}
},
"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/湖南石化青年体质检测.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = 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",
"list1 = []\n",
"for k, v in dict1.items():\n",
" if k in dict2.keys() and k not in dict3.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（非湖南青年）.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": "markdown",
"id": "83db1501-6625-4e72-9a5e-2184b8e309e9",
"metadata": {},
"source": [
"## 核对重名人员"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "dd7557bf-6f1e-4d01-aa93-5a4ad46a57a5",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-11T06:12:49.795632Z",
"iopub.status.busy": "2024-12-11T06:12:49.794818Z",
"iopub.status.idle": "2024-12-11T06:12:49.967842Z",
"shell.execute_reply": "2024-12-11T06:12:49.967393Z",
"shell.execute_reply.started": "2024-12-11T06:12:49.795561Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3437581 李成伟\n",
"3526193 李可\n",
"3464205 胡雨丹\n",
"1010 邱亮\n",
"1012 吴磊\n",
"3464081 刘权\n",
"3125625 宋霰\n",
"1020 贾俊\n",
"1022 徐敬\n",
"1023 彭一夫\n",
"1024 刘至清\n",
"1053 刘志刚\n",
"1058 杨红\n",
"1069 李鑫\n",
"1144 黄英杰\n"
]
}
],
"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/长炼医院人员2024.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"\n",
"filename = 'data/湖南石化青年体质检测.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
" \n",
"set1 = set()\n",
"\n",
"for k, v in dict2.items():\n",
" set1.add(v['name'])\n",
"\n",
"for k, v in dict1.items():\n",
" if v['name'] in set1:\n",
" print(k,v['name'])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "ded0ac64-9ba2-4d64-9617-e0961b437d4e",
"metadata": {
"execution": {
"iopub.execute_input": "2024-12-11T06:33:09.011061Z",
"iopub.status.busy": "2024-12-11T06:33:09.010467Z",
"iopub.status.idle": "2024-12-11T06:33:09.030379Z",
"shell.execute_reply": "2024-12-11T06:33:09.029760Z",
"shell.execute_reply.started": "2024-12-11T06:33:09.011010Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"29\n",
"29\n"
]
}
],
"source": [
"import json\n",
"import time\n",
"import csv\n",
"\n",
"filename = '../item1.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（汇总）.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"filename = 'data/places_result_20241206.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(0417前）.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": "code",
"execution_count": null,
"id": "7583ad54-3e66-4ef8-ae51-f01eda2bf647",
"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
}
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