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jupyter/体测单位/镇海.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "92891af2-e909-4b8e-a08a-b5b5e4a1c732",
"metadata": {
"jp-MarkdownHeadingCollapsed": true
},
"source": [
"# 体质测试2024年"
]
},
{
"cell_type": "markdown",
"id": "338fb8da-815a-4536-ae91-4f461ba9401f",
"metadata": {},
"source": [
"## 体测人员导入"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ba24132c-133f-4508-8fe7-e68d1908b6e9",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/镇海参加测试人员名单(合并).xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = int(sheet.cell(n, 1).value)\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 2).value\n",
" dict1['sex'] = sheet.cell(n, 3).value\n",
" dict1['unit'] = sheet.cell(n, 5).value\n",
" if sheet.cell(n, 6).value is not None:\n",
" dict1['gh'] = sheet.cell(n, 6).value\n",
" dict1['birth'] = str(sheet.cell(n, 4).value).replace('/','-').split(' ')[0] \n",
" if sheet.cell(n, 7).value is not None:\n",
" dict1['phone'] = str(sheet.cell(n,7).value)\n",
" person[code] = dict1\n",
"filename = 'data/镇海(合并).json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "10ddfd3b-697c-4459-8bed-147b22f88239",
"metadata": {},
"source": [
"## 生成读卡系统文件"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "63ab2d5b-3a0a-4ac7-a3e7-b3a34e621e98",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/镇海.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"for k, v in dict1.items():\n",
" dict2 = {}\n",
" #if dict1['sex'] =='男':\n",
" # sex = 1\n",
" \n",
" dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n",
" list1.append(dict2)\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/card_镇海.json\", \"w\",encoding = 'utf-8') as file:\n",
" file.write(json_data) \n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "b6dd08b0-f58c-4dc1-86a9-e7b2b84478c3",
"metadata": {},
"source": [
"## 获取人员测试成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5d864909-d10f-461d-8e6e-dc5c43613576",
"metadata": {},
"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/镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"filename = 'data/places_result_20240922.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]['sub_unit'] = dict1[user]['sub_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_镇海(合并).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": "a08c6b65-a390-451b-b1a5-fc474db40035",
"metadata": {},
"source": [
"## 导出测试人员信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bc79f0d2-62a2-40c8-bd74-9c7ff17bec8e",
"metadata": {},
"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','部门','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_镇海.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/镇海体测人员.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",
" list2.append(dict2[k]['gwxl'])\n",
" list2.append(dict2[k]['gzz'])\n",
" list1.append(list2)\n",
"filename = 'data/镇海体测情况表.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "0c2dfa71-8680-4ec6-938d-d37eeba4d4f9",
"metadata": {},
"source": [
"## 统计未体测人员明细表"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cf22739a-5cf3-47fd-b87a-158a2e2d5a95",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"filename = 'data/result_镇海.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/镇海1.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"\n",
"list1 = []\n",
"\n",
"i = 1\n",
"for k, v in dict2.items(): \n",
" if k not in dict1.keys():\n",
" list2 = [i,k,v['name'],v['unit']]\n",
" i+=1\n",
" list1.append(list2)\n",
"#print(list1)\n",
"filename = f'data/镇海未测试人员名单(截至20240922).xlsx'\n",
"title = ['序号','员工编号','姓名','部门']\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": "286a65eb-995f-4183-a4e5-6d907ba21151",
"metadata": {},
"source": [
"## 清理重复人员"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f4dade65-f760-4220-8a65-39843688a60a",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/镇海.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"print(len(dict1))\n",
"dict2 = {}\n",
"for k, v in dict1.items():\n",
" if 'phone' in v.keys():\n",
" dict2.setdefault(k,{})\n",
" dict2[k]['name'] = v['name']\n",
" dict2[k]['phone'] = v['phone']\n",
"\n",
"list1 = []\n",
"for k, v in dict2.items():\n",
" i = 0\n",
" for k1, v1 in dict1.items():\n",
" if v['name']== v1['name'] and v['phone'] == v1['phone'] and k1 != k:\n",
" list1.append(max(int(k),int(k1)))\n",
"for item in set(list1):\n",
" del dict1[str(item)]\n",
"print(len(dict1))\n",
"filename = 'data/镇海1.json'\n",
"\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False) \n"
]
},
{
"cell_type": "markdown",
"id": "e513b5bb-8a4e-412a-880b-1ae36e059bfd",
"metadata": {},
"source": [
"## 转换报告格式"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f038e8d-dd57-4880-8726-6dfa86fbc4a2",
"metadata": {},
"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/镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"filename = 'data/places_result_20240922.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_镇海(合并).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": "de2eec6d-a74e-47e1-ab7a-c7f6eda80a20",
"metadata": {},
"source": [
"## 生成完善得分"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "763aa68a-da54-4745-a759-4399aba10f7e",
"metadata": {},
"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",
"\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_镇海(合并).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_镇海(合并).json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print('ok!') "
]
},
{
"cell_type": "markdown",
"id": "bb0f8c6f-5088-4c4d-a253-9c207745ef25",
"metadata": {},
"source": [
"## 生成体测成绩明细表"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5cff3c83-b3cb-4c69-97a9-82e523374f6b",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"items = ['lung','grip','flexion','jump','pushup','situp','balance','reaction','step']\n",
"bmi = ['height','weight']\n",
"title = ['编号','姓名','性别','单位/部门','身高','体重','bmi','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_镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"list1 = []\n",
"for k, v in dict1.items(): #print(k,dict2[str(k)]['name'])\n",
" list2 = []\n",
" list2.append(str(k).rjust(5,'0'))\n",
" list2.append(dict1[k]['name']) \n",
" list2.append(dict1[k]['sex'])\n",
" list2.append(dict1[k]['unit'])\n",
" i = 0\n",
" if 'bmi' in dict1[k].keys():\n",
" list2.append(dict1[k]['height']['成绩'])\n",
" list2.append(dict1[k]['weight']['成绩'])\n",
" list2.append(dict1[k]['bmi']['score'])\n",
" i+=1\n",
" else:\n",
" list2.append('') \n",
" list2.append('') \n",
" list2.append('') \n",
" \n",
" \n",
" for item in items:\n",
" if item in dict1[k].keys():\n",
" list2.append(dict1[k][item]['成绩'])\n",
" list2.append(dict1[k][item]['score']) \n",
" i+=1\n",
" elif item =='name':\n",
" list2.append(dict1[k][item])\n",
" else:\n",
" list2.append('') \n",
" list2.append('') \n",
" if i>2:\n",
" list1.append(list2)\n",
"filename = 'data/镇海体测情况明细表.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)\n",
"print('ok') "
]
},
{
"cell_type": "markdown",
"id": "723ae3d7-ec16-4dc6-91e2-eeeea6ffe081",
"metadata": {},
"source": [
"## 生成报告"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "90faac13-492d-4b3d-bb21-c228af6d9864",
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"headers = {\n",
" \"Content-Type\": \"application/json; charset=UTF-8\"\n",
" }\n",
"filename = 'data/result_镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"file_path ='./镇海石化/'\n",
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
"i=0\n",
"list2 = []\n",
"for k, v in dict1.items():\n",
" list1 = []\n",
" mydata = {}\n",
" \n",
" id = str(k).rjust(4,\"0\")\n",
" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
" mydata['title'] = '中国石化镇海炼化公司'\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",
" survey_list = ['tcm','psy','spine']\n",
" for item in survey_list:\n",
" if item in v.keys():\n",
" mydata.setdefault('surveys',{})\n",
" mydata['surveys'][item] = v[item]\n",
" \n",
" \n",
" #mydata['fits'] = {}\n",
" for item in list_item:\n",
" if item in v.keys():\n",
" mydata.setdefault('fits',{})\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 or len(mydata['surveys']) >0:\n",
" if len(mydata['fits']) >2 : \n",
" list1.append(mydata)\n",
" list2.append([k,v['name']])\n",
" i+=1\n",
" x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
" #print(id,v['name'],x.text)\n",
" #print(mydata)\n",
" #x.close()\n",
"print(i)"
]
},
{
"cell_type": "markdown",
"id": "82c1eaea-89ad-444a-8dad-07f438c739cc",
"metadata": {},
"source": [
"## 统计报告人员信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "61c731bc-6117-4a9f-8bfa-66f820e49fc4",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import glob\n",
"from pathlib import Path\n",
"import openpyxl\n",
"\n",
"filename = 'data/镇海.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files/345321'\n",
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
"dict2 = {}\n",
"for fn in fls:\n",
" \n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" #fi_name =Path(fn).stem\n",
" code = int(fi_name)\n",
" dict2[str(code)] = dict1[str(code)]\n",
"filename = 'data/镇海体测人员.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print(len(dict2)) \n",
"list1 = []\n",
"for k, v in dict2.items(): \n",
" list2 = []\n",
" if 'gh' in v.keys():\n",
" gh = v['gh']\n",
" else:\n",
" gh = ''\n",
" if 'phone' in v.keys():\n",
" phone = v['phone']\n",
" else:\n",
" phone = ''\n",
" list2 = [k,v['name'],v['sex'],v['birth'],v['unit'],gh,phone]\n",
" list1.append(list2)\n",
"#print(list1)\n",
"filename = 'data/镇海参加测试人员名单.xlsx'\n",
"title = ['序号','员工编号','姓名','部门']\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": "fc0f353c-1021-4c8c-bb7c-7a4abb609836",
"metadata": {},
"source": [
"## 补充报告人员信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fa963fb6-b47d-4b75-9109-6cda89218182",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"import json\n",
"import glob\n",
"from pathlib import Path\n",
"import openpyxl\n",
"\n",
"\n",
"filename = 'data/镇海体测人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"wb = openpyxl.load_workbook('data/镇海炼化参加测试人员名单(分析用).xlsx')\n",
"sheet = wb.active\n",
"for n in range(2, sheet.max_row+1):\n",
" if sheet.cell(n, 12).value is not None:\n",
" code = int(sheet.cell(n, 1).value)\n",
" if sheet.cell(n, 12).value is not None:\n",
" dict1[str(code)]['gwlb'] = sheet.cell(n, 12).value\n",
" dict1[str(code)]['gwxl'] = sheet.cell(n, 9).value\n",
" dict1[str(code)]['gzz'] = sheet.cell(n, 11).value\n",
"\n",
"with open(filename, 'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False) \n",
"print('ok!') \n"
]
},
{
"cell_type": "markdown",
"id": "385285b8-fdb3-421d-afbf-c13e4f55bb46",
"metadata": {},
"source": [
"## 核验报告人员信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c6195bc3-64bc-4f52-8ebc-ba16fd222f85",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/镇海炼化参加测试人员名单.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = int(sheet.cell(n, 1).value)\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 2).value\n",
" dict1['sex'] = sheet.cell(n, 3).value\n",
" dict1['unit'] = sheet.cell(n, 5).value\n",
" if sheet.cell(n, 6).value is not None:\n",
" dict1['gh'] = sheet.cell(n, 6).value\n",
" dict1['birth'] = str(sheet.cell(n, 4).value).replace('/','-').split(' ')[0] \n",
" if sheet.cell(n, 7).value is not None:\n",
" dict1['phone'] = str(sheet.cell(n,7).value)\n",
" if len(str(sheet.cell(n,7).value))<11:\n",
" print(code,sheet.cell(n, 2).value)\n",
" person[code] = dict1\n",
"filename = 'data/镇海炼化参加测试人员.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print(len(person))"
]
},
{
"cell_type": "markdown",
"id": "7e551660-e85f-4da2-8224-042784033ed5",
"metadata": {},
"source": [
"## 生成查询信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "299c1d41-7634-4703-8411-08f175df4e16",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import os,sys,shutil\n",
"import json\n",
"import math\n",
"import glob\n",
"import random\n",
"from pathlib import Path\n",
"import pymongo\n",
"\n",
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
"mydb = myclient[\"baogao\"]\n",
"mycol = mydb[\"pdf\"]\n",
"\n",
"place_id = 345321\n",
"\n",
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files'\n",
"fls = glob.glob(f'{fi_path}/{str(place_id)}/*.pdf')\n",
"\n",
"filename = 'data/镇海炼化参加测试人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"for fn in fls:\n",
" dict2 = {}\n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" #fi_name =Path(fn).stem\n",
" code = int(fi_name)\n",
" dxm = dict1[str(code)]['gh']\n",
" dict2 = {'place_id':place_id,'code':dxm,'fn':Path(fn).name}\n",
" list2.append(dict2)\n",
" i +=1\n",
"x = mycol.insert_many(list2)\n",
"print('ok') "
]
},
{
"cell_type": "markdown",
"id": "e923022e-aef7-4c8e-84f9-b853e53ff820",
"metadata": {},
"source": [
"## 根据工号生成查询信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f709fd4a-d0b0-44a9-a782-0c1ffd43f6b8",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"filename = 'data/镇海炼化参加测试人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"list2 = []\n",
"set1 = set()\n",
"for k, v in dict1.items():\n",
" if 'gh' in v.keys():\n",
" gh = v['gh']\n",
" if gh not in list1:\n",
" list1.append(v['gh'])\n",
" else:\n",
" list2.append(gh)\n",
"print(list2)"
]
},
{
"cell_type": "markdown",
"id": "d9464f81-9228-403a-9d78-090fb4ce0faa",
"metadata": {},
"source": [
"## 体测报告按部门分类"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7eac364f-0fde-4853-9d2b-8c4c0c59a341",
"metadata": {},
"outputs": [],
"source": [
"import os,sys,shutil\n",
"import json\n",
"import glob\n",
"from pathlib import Path\n",
"\n",
"fi_path = '/home/songyi/pdf-typescript/镇海石化'\n",
"new_path = 'file/镇海石化'\n",
"old = []\n",
"dict2 = {}\n",
"\n",
"filename = 'data/镇海炼化参加测试人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
"for fn in fls:\n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" code = int(fi_name)\n",
" unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
" unit_path.mkdir(parents = True, exist_ok = True)\n",
" n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
" if not os.path.exists(n_name):\n",
" shutil.copyfile(fn,n_name)"
]
},
{
"cell_type": "markdown",
"id": "d7bb270c-cc9e-413b-af36-17c33692e289",
"metadata": {},
"source": [
"## 生成体测报告打印明细表"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d88bd5c4-1df3-457b-b65d-61692c45e7bd",
"metadata": {},
"outputs": [],
"source": [
"import os,sys,shutil\n",
"import json\n",
"import glob\n",
"from pathlib import Path\n",
"import openpyxl\n",
"\n",
"fi_path = '/home/songyi/pdf-typescript/镇海石化'\n",
"\n",
"filename = 'data/镇海炼化参加测试人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
"list1 = []\n",
"title = ['测试编号','姓名','性别','部门']\n",
"for fn in fls:\n",
" list2 = []\n",
" fi_name =Path(fn).stem.split('-')[0] \n",
" code = int(fi_name)\n",
" sex = dict1[str(code)]['sex']\n",
" unit = dict1[str(code)]['unit']\n",
" list2 = [fi_name,Path(fn).stem.split('-')[1],sex,unit]\n",
" \n",
" list1.append(list2)\n",
"\n",
"filename = 'data/镇海石化体测报告明细表.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) \n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "6b521daf-f9dc-4579-9400-d8ab857bb166",
"metadata": {
"jp-MarkdownHeadingCollapsed": true
},
"source": [
"# 体质测试综合报告数据分析"
]
},
{
"cell_type": "markdown",
"id": "83203d08-46ca-45f6-8204-0c8e35f754b6",
"metadata": {},
"source": [
"## 清理报告数据"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cccc2e43-7a73-48ec-8540-06b4d59f8ceb",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"filename = 'data/result_镇海(合并).json'\n",
"with open(filename,'r',encoding = 'utf-8') 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",
"#fiie_path ='./138/'\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",
" mydata['score'] = round(score/len(mydata['fits']),2)\n",
" if len(mydata['fits']) >2:\n",
" dict2[str(k)] = mydata\n",
"filename = f'data/data_镇海(合并).json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print('ok!') "
]
},
{
"cell_type": "markdown",
"id": "1c0bca93-d8a7-42ba-9a2c-50d3493c802f",
"metadata": {},
"source": [
"## 报告按照工作制分类"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a550ecd7-da8e-41b6-8b8f-8bc144d48bfe",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"filename = 'data/result_镇海2.json'\n",
"with open(filename,'r',encoding = 'utf-8') as fl:\n",
" dict1 = json.load(fl)\n",
"filename = 'data/镇海体测人员.json'\n",
"with open(filename,'r',encoding = 'utf-8') as fl:\n",
" dict3 = 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",
"#fiie_path ='./138/'\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",
" if dict3[k]['gzz'] == '倒班':\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",
" mydata['score'] = round(score/len(mydata['fits']),2)\n",
" if len(mydata['fits']) >2:\n",
" dict2[str(k)] = mydata\n",
"filename = f'data/data_镇海_倒班.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print(len(dict2)) "
]
},
{
"cell_type": "markdown",
"id": "c3bcd7ec-1d66-40c6-a27d-1c73e6eef695",
"metadata": {},
"source": [
"## 计算平均成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d5721244-b5f5-4577-bae8-2e6c5bd8e4da",
"metadata": {},
"outputs": [],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"filename = 'data/data_镇海(合并).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/(f+m),4)}分,总体:{(f+m)}人')"
]
},
{
"cell_type": "markdown",
"id": "a7ba7d25-b7a0-4641-a218-b4569d31acb1",
"metadata": {},
"source": [
"## 计算测试等级"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cff50f06-3221-4340-950f-3a24073b8565",
"metadata": {},
"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))\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl) \n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "16a0d09b-2128-4df4-9745-954f48384244",
"metadata": {},
"source": [
"### 计算各年龄段测试等级(女)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6baf0ff2-cdfa-4396-bcf8-3e23a18670dc",
"metadata": {},
"outputs": [],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"\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",
"dict3 = {}\n",
"for item in nld:\n",
" di = item[0]\n",
" gao = item[1]\n",
" age = f'{di}-{gao}'\n",
" dict3.setdefault(age,{})\n",
" i = 0 \n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if v['age'] in range(di,gao+1): \n",
" dict3[age].setdefault(v['level'],0)\n",
" if v['sex'] == '女':\n",
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
" \n",
"for k, v in dict3.items():\n",
" print(k,v)"
]
},
{
"cell_type": "markdown",
"id": "79fb3eab-e8d4-42bb-9ba4-8402f3b82b54",
"metadata": {},
"source": [
"### 计算各年龄段测试等级(男)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2979cf80-5268-4754-ab8a-11a539315e92",
"metadata": {},
"outputs": [],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"\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",
"dict3 = {}\n",
"for item in nld:\n",
" di = item[0]\n",
" gao = item[1]\n",
" age = f'{di}-{gao}'\n",
" dict3.setdefault(age,{})\n",
" i = 0 \n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if v['age'] in range(di,gao+1): \n",
" dict3[age].setdefault(v['level'],0)\n",
" if v['sex'] == '男':\n",
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
" \n",
"for k, v in dict3.items():\n",
" print(k,v)"
]
},
{
"cell_type": "markdown",
"id": "9a38fc15-579c-42e9-a23c-1050a96e0cf8",
"metadata": {},
"source": [
"## 根据年龄汇总人员信息及成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8a7cb3b0-d7be-44ac-a1ec-40bdcf29e83b",
"metadata": {},
"outputs": [],
"source": [
"nld = [[16,24],[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 = 0\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",
" if i ==0:\n",
" print(f'{di}~{gao}岁平均成绩:0分,人数:0人,男性:{m}人')\n",
" else:\n",
" print(f'{di}~{gao}岁平均成绩:{round(score/i,2)}分,人数:{i}人,男性:{m}人')"
]
},
{
"cell_type": "markdown",
"id": "48debe3b-d0ec-41e8-93ef-921b8e013aa7",
"metadata": {},
"source": [
"### 根据年龄汇总人员信息及成绩(男)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c5bb03ca-b7ee-4564-b425-8513e1bff081",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\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 = 0\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) and v['sex'] == '男':\n",
" score = score+v['score']\n",
" i+=1\n",
" if i ==0:\n",
" print(f'{di}~{gao}岁平均成绩:0分,人数:{i}人') \n",
" else:\n",
" print(f'{di}~{gao}岁平均成绩:{round(score/i,2)}分,人数:{i}人')"
]
},
{
"cell_type": "markdown",
"id": "92bb0683-81ea-4b90-8b74-4a2f43b4835c",
"metadata": {},
"source": [
"### 根据年龄汇总人员信息及成绩(女)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bf333998-230c-4365-aadc-b0d1be073b39",
"metadata": {},
"outputs": [],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\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 = 0\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) and v['sex'] == '女':\n",
" score = score+v['score']\n",
" i+=1\n",
" if i ==0:\n",
" print(f'{di}~{gao}岁平均成绩:0分,人数:{i}人') \n",
" else:\n",
" print(f'{di}~{gao}岁平均成绩:{round(score/i,2)}分,人数:{i}人')"
]
},
{
"cell_type": "markdown",
"id": "026d11e4-7f3d-4be5-9fa0-fa3699969c6b",
"metadata": {},
"source": [
"## 计算各项目成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "352c6c29-8929-4210-84c5-8dbc3d5ffeee",
"metadata": {},
"outputs": [],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"items = ['BMI','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",
"for item in items:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items(): \n",
" if item in v['fits'].keys():\n",
" n = n + 1\n",
" score =score + int(v['fits'][item]['score'])\n",
" print(item,round(score/n,2),n)"
]
},
{
"cell_type": "markdown",
"id": "a13d5644-7cd1-4943-bce9-c6863f75b986",
"metadata": {},
"source": [
"## 按照部门计算平均成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "97f5a1cf-341e-4b99-9549-b6a3fb165849",
"metadata": {},
"outputs": [],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"depart = []\n",
"for k, v in dict1.items():\n",
" if v['unit'] not in depart:\n",
" depart.append(v['unit'])\n",
"\n",
"for item in depart:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items():\n",
" if item == v['unit']:\n",
" score = score + v['score']\n",
" n = n +1\n",
" if n>0:\n",
" print(item,round(score/n,2),n)\n",
" else:\n",
" print(item,0,n)"
]
},
{
"cell_type": "markdown",
"id": "85b3a695-86db-4aec-95f4-33f3b628e548",
"metadata": {},
"source": [
"### 按照部门计算平均成绩(男性)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3beaab27-ca90-4e09-b2d2-590fd7bac51d",
"metadata": {},
"outputs": [],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"depart = []\n",
"for k, v in dict1.items():\n",
" if v['unit'] not in depart:\n",
" depart.append(v['unit'])\n",
"\n",
"for item in depart:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items():\n",
" if item == v['unit'] and v['sex'] == '男':\n",
" score = score + v['score']\n",
" n = n +1 \n",
" if n>0:\n",
" print(item,round(score/n,2),n)\n",
" else:\n",
" print(item,0,n)"
]
},
{
"cell_type": "markdown",
"id": "d8e995d6-3ddb-4b92-8255-530e8a3da179",
"metadata": {},
"source": [
"## 计算部门成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a959c1b8-86fc-4fca-8595-4278135e95b8",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"items = ['BMI','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 = 'data/data_镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"dict3 = {}\n",
"\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" dict3.setdefault(unit,{})\n",
" for item in items:\n",
" dict3[unit].setdefault(item,{})\n",
" dict3[unit][item].setdefault('score',0)\n",
" dict3[unit][item].setdefault('count',0)\n",
" for k1,v1 in v['fits'].items():\n",
" if k1 in items:\n",
" dict3[unit][k1]['score']+=v1['score']\n",
" dict3[unit][k1]['count']+=1\n",
"\n",
"for k, v in dict3.items():\n",
" print(k)\n",
" for k1, v1 in v.items():\n",
" print(k1,v1['score'],v1['count'])"
]
},
{
"cell_type": "markdown",
"id": "7092779e-ce30-4d1c-8e7b-a14011daee93",
"metadata": {},
"source": [
"## 计算部门等级"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "81195537-5a43-4822-a1b9-a08b7baee05e",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"items = ['优秀','良好','合格','不合格'] \n",
"filename = 'data/data_镇海(合并).json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"\n",
"dict3 = {}\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" dict3.setdefault(unit,{})\n",
" for item in items:\n",
" dict3[unit].setdefault(item,0)\n",
"\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" #dict3.setdefault(unit,{})\n",
" #for item in items:\n",
" #dict3[unit].setdefault(v['level'],0)\n",
" dict3[unit][v['level']] +=1\n",
"for k, v in dict3.items():\n",
" print(k,v['优秀'],v['良好'],v['合格'],v['不合格'])"
]
},
{
"cell_type": "markdown",
"id": "4df1e70c-e359-4b4a-b2ae-2900ae25ded2",
"metadata": {
"execution": {
"iopub.execute_input": "2025-10-25T08:36:22.140778Z",
"iopub.status.busy": "2025-10-25T08:36:22.140431Z",
"iopub.status.idle": "2025-10-25T08:36:22.145537Z",
"shell.execute_reply": "2025-10-25T08:36:22.144522Z",
"shell.execute_reply.started": "2025-10-25T08:36:22.140742Z"
}
},
"source": [
"# 体质测试2025年"
]
},
{
"cell_type": "markdown",
"id": "0dbcde66-5a57-4b6d-97d3-30159b606807",
"metadata": {},
"source": [
"## 体测人员导入"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0a6a661d-3780-4ae4-a975-821eae376f7a",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/镇海人员2025.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = sheet.cell(n, 5).value\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 2).value\n",
" dict1['sex'] = sheet.cell(n, 3).value\n",
" dict1['birth'] = str(sheet.cell(n, 6).value).replace('/','-').split(' ')[0] \n",
" dict1['unit'] = sheet.cell(n, 7).value\n",
" dict1['phone'] = sheet.cell(n, 4).value\n",
" person[code] = dict1\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print(len(person),'ok')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2af3b485-743e-40ca-8caa-5eecd572c2a5",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/镇海人员信息确认表.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = sheet.cell(n, 1).value.lower()\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 2).value\n",
" dict1['sex'] = sheet.cell(n, 3).value\n",
" dict1['birth'] = str(sheet.cell(n, 5).value).replace('/','-').split(' ')[0] \n",
" dict1['unit'] = sheet.cell(n, 4).value\n",
" if sheet.cell(n,6).value is not None:\n",
" dict1['phone'] = sheet.cell(n, 6).value\n",
" person[code] = dict1\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print(len(person),'ok')"
]
},
{
"cell_type": "markdown",
"id": "c938346f-711c-4cd7-b2f1-3776df5a00b8",
"metadata": {},
"source": [
"## 生成读卡系统文件"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "da037e81-96a8-475e-9ad7-21ab92285b85",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"for k, v in dict1.items():\n",
" dict2 = {}\n",
" #if dict1['sex'] =='男':\n",
" # sex = 1\n",
" \n",
" dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n",
" list1.append(dict2)\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/card_镇海2025.json\", \"w\",encoding = 'utf-8') as file:\n",
" file.write(json_data) \n",
"print(len(list1),'ok')"
]
},
{
"cell_type": "markdown",
"id": "165f14d8-a973-463c-87cd-8c0c0de6a177",
"metadata": {},
"source": [
"## 合并读卡系统文件"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "505fce63-ed92-4f63-82da-7207b015dab4",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/data_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" list1 = json.load(fl)\n",
"for item in list1:\n",
" code = item['id'].lower()\n",
" if code not in dict1.keys():\n",
" print(code,item['name'],item['unit'])\n",
" code = code.lower()\n",
" dict1.setdefault(code,{})\n",
" dict1[code]['name'] = item['name']\n",
" dict1[code]['sex'] = item['gender']\n",
" dict1[code]['unit'] = item['unit']\n",
" dict1[code]['birth'] = item['birth']\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False)\n",
"print(len(dict1),'ok')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f1aefe1c-150d-4a55-98b5-3a72e9510e5d",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/data_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" list1 = json.load(fl)\n",
"for item in list1:\n",
" code = item['id'].lower()\n",
" dict1[code]['name'] = item['name']\n",
" dict1[code]['sex'] = item['gender']\n",
" dict1[code]['unit'] = item['unit']\n",
" dict1[code]['birth'] = item['birth']\n",
"filename = 'data/镇海人员2025-1.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False)\n",
"print(len(dict1),'ok')"
]
},
{
"cell_type": "markdown",
"id": "a5965545-1f5b-4ba2-b1b2-81a56572af74",
"metadata": {},
"source": [
"## 核对人员信息"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "a8438d1b-ec3d-41e3-9c28-d44e88378c75",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-07T05:30:46.511261Z",
"iopub.status.busy": "2025-11-07T05:30:46.510560Z",
"iopub.status.idle": "2025-11-07T05:30:46.695916Z",
"shell.execute_reply": "2025-11-07T05:30:46.695456Z",
"shell.execute_reply.started": "2025-11-07T05:30:46.511196Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1564 ok\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/镇海人员信息确认表.xlsx')\n",
"sheet = wb.active\n",
"person = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = sheet.cell(n, 1).value\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 2).value\n",
" dict1['sex'] = sheet.cell(n, 3).value\n",
" dict1['birth'] = str(sheet.cell(n, 5).value).replace('/','-').split(' ')[0] \n",
" dict1['unit'] = sheet.cell(n, 4).value\n",
" if sheet.cell(n, 6).value is not None:\n",
" dict1['phone'] = sheet.cell(n, 6).value\n",
" person[code] = dict1\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print(len(person),'ok')"
]
},
{
"cell_type": "markdown",
"id": "74f568d1-0bd9-4028-8e6a-e0c25ead7958",
"metadata": {},
"source": [
"## 导入手工数据"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "772330af-6224-43ad-9727-79854c33231c",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/镇海项目手工成绩.xlsx')\n",
"sheet = wb.active\n",
"filename = 'data/result_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl) \n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = str(sheet.cell(n, 1).value)\n",
" item = str(sheet.cell(n, 2).value)\n",
" mark = str(sheet.cell(n, 3).value)\n",
" dict2[code].setdefault(item,{})\n",
" dict2[code][item]['成绩'] = mark\n",
" \n",
"filename = 'data/result_镇海2025-1.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl, ensure_ascii=False) \n",
"print(len(re_ta)) "
]
},
{
"cell_type": "markdown",
"id": "065cb133-3c61-46bd-bf81-7afa2c9be9e0",
"metadata": {},
"source": [
"## 获取人员测试成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "289e4e1d-c80d-46f9-9015-fc4c139bc99d",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import datetime\n",
"import csv\n",
"from datetime import date\n",
"import my_module1 as My\n",
"\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"filename = 'data/marks_20251031.csv'\n",
"re_ta = My.get_result(filename,dict1)\n",
"\n",
"\n",
"filename = 'data/result_镇海2025.json'\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": "f9df8146-0430-42b5-b6d0-992c71ee645b",
"metadata": {},
"source": [
"## 修正测试成绩"
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "9caa8291-7d48-483b-992a-45f244567600",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-07T06:15:57.737800Z",
"iopub.status.busy": "2025-11-07T06:15:57.737061Z",
"iopub.status.idle": "2025-11-07T06:15:57.818225Z",
"shell.execute_reply": "2025-11-07T06:15:57.817635Z",
"shell.execute_reply.started": "2025-11-07T06:15:57.737730Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1564\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"from datetime import date\n",
"\n",
"\n",
"filename = 'data/result_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl) \n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = json.load(fl) \n",
"dict1 = {}\n",
"for k, v in dict2.items():\n",
" code = k.upper()\n",
" dict1[code] = v\n",
" dict1[code]['unit'] = dict3[code]['unit']\n",
"filename = 'data/result_镇海2025-1.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False) \n",
"print(len(re_ta))\n",
" "
]
},
{
"cell_type": "markdown",
"id": "15d7fae0-76a3-4443-8c2c-94ec7b8f052c",
"metadata": {},
"source": [
"## 生成测试得分"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "49d15e27-6029-4557-a17a-7e7a426f7e5f",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import time\n",
"import my_module as My\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_镇海2025-1.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 'bmi' in v.keys():\n",
" #bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
" bmi_data = v['bmi']['成绩']\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'] = My.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",
" #print(k,v['name'])\n",
" dict2[k][item_en]['score'] = My.cal_score(data1)\n",
" #print(k,v[item_en]['成绩'],cal_score(data1))\n",
"\n",
"filename = f'data/result_镇海2025.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2,fl , ensure_ascii=False) \n",
"print('ok!') "
]
},
{
"cell_type": "markdown",
"id": "c1ef03ac-6970-4d33-9d30-fc2ffe4e7c52",
"metadata": {},
"source": [
"## 导出测试人员信息"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8ed6705e-b4f6-419e-b94b-4c391fed4551",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"items = ['lung','grip','flexion','jump','pushup','situp','balance','reaction','step']\n",
"title = ['编号','姓名','性别','单位','部门','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_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/镇海人员2025.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",
" list2.append(dict2[k]['birth'])\n",
" if 'phone' in v.keys():\n",
" list2.append(dict2[k]['phone'])\n",
" else:\n",
" list2.append('')\n",
" \n",
" if 'bmi' in v.keys():\n",
" height = v['bmi']['成绩'].split(',')[0]\n",
" weight = v['bmi']['成绩'].split(',')[1]\n",
" list2.append(height)\n",
" list2.append(weight)\n",
" else:\n",
" list2.append('')\n",
" list2.append('')\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",
" \n",
" list1.append(list2)\n",
"filename = 'data/镇海体测情况表(2025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": "d6d6b47e-386c-4cee-a4d6-6dbe4f415490",
"metadata": {},
"source": [
"## 统计各部门测试情况"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a0c85107-7c75-462c-8f77-aea787d2100f",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"filename = 'data/result_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"\n",
"dict3 = {}\n",
"for k, v in dict2.items():\n",
" unit = v['unit']\n",
" #sub_unit = v['sub_unit']\n",
" dict3.setdefault(unit,{})\n",
" dict3[unit].setdefault('人数',0)\n",
" dict3[unit].setdefault('体测人数',0)\n",
" #dict3[unit].setdefault(sub_unit,0)\n",
" #dict3[unit][sub_unit] = dict3[unit][sub_unit] + 1\n",
" dict3[unit]['人数'] = dict3[unit]['人数'] + 1\n",
"\n",
"title =['单位','体测人数']\n",
"list1 = []\n",
"for k,v in dict1.items(): \n",
" unit = v['unit']\n",
" #sub_unit = v['sub_unit']\n",
" #dict3[unit][sub_unit] = dict3[unit][sub_unit] - 1\n",
" dict3[unit].setdefault('体测人数',0)\n",
" dict3[unit]['体测人数'] = dict3[unit]['体测人数'] + 1\n",
"for k, v in dict3.items():\n",
" list2 = [k,v['人数'],v['体测人数']]\n",
" list1.append(list2)\n",
"\n",
"filename = 'data/镇海部门测试情况(截至20251031).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": "0d7d8dd1-45f7-455d-8db3-38febc2a2395",
"metadata": {},
"source": [
"## 统计未体测人员明细表"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cc39720e-3be5-482f-a8d1-4495cf103b4f",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"filename = 'data/result_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/镇海人员2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
"\n",
"list1 = []\n",
"\n",
"i = 1\n",
"for k, v in dict2.items(): \n",
" if k not in dict1.keys():\n",
" list2 = [i,k,v['name'],v['unit']]\n",
" i+=1\n",
" list1.append(list2)\n",
"#print(list1)\n",
"filename = f'data/镇海未测试人员名单(截至20251031).xlsx'\n",
"title = ['序号','员工编号','姓名','部门']\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": "3e0e3b48-12f1-42f0-ba3c-f949857d29f7",
"metadata": {},
"source": [
"## 体测报告导入数据库"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8c929073-2c32-4ecf-93fa-f3bf224bcb31",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"import os,sys,shutil\n",
"import json\n",
"import math\n",
"import glob\n",
"import random\n",
"from pathlib import Path\n",
"import pymongo\n",
"\n",
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
"mydb = myclient[\"baogao\"]\n",
"\n",
"place_id = 1\n",
"place_code = \"20\"\n",
"\n",
"fi_path = '/home/songyi/python/mycrm/flask/pdf/files'\n",
"fls = glob.glob(f'{fi_path}/{str(place_id)}/*.pdf')\n",
"\n",
"\n",
"for fn in fls:\n",
" dict2 = {}\n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" #fi_name =Path(fn).stem\n",
" code = int(fi_name)\n",
" dxm = list1[i]\n",
" dict2 = {'place_id':place_id,'code':dxm,'fn':Path(fn).name}\n",
" list2.append(dict2)\n",
" i +=1\n",
"x = mycol.insert_many(list2)\n",
"print(len(list2),'ok') "
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "3b73e071-62ad-41fb-8b9d-57893dbf8a6f",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-09T05:50:17.521854Z",
"iopub.status.busy": "2025-11-09T05:50:17.521109Z",
"iopub.status.idle": "2025-11-09T05:50:17.537693Z",
"shell.execute_reply": "2025-11-09T05:50:17.536539Z",
"shell.execute_reply.started": "2025-11-09T05:50:17.521785Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[{'place_id': 1, 'code': '016368', 'fn': '016368-陈兴旺.pdf'}, {'place_id': 1, 'code': '013403', 'fn': '013403-孙震.pdf'}, {'place_id': 1, 'code': '008553', 'fn': '008553-张国栋.pdf'}, {'place_id': 1, 'code': '015775', 'fn': '015775-张永战.pdf'}, {'place_id': 1, 'code': '015867', 'fn': '015867-高再玲.pdf'}, {'place_id': 1, 'code': '015770', 'fn': '015770-许丹萍.pdf'}, {'place_id': 1, 'code': '021574', 'fn': '021574-杨子敬.pdf'}, {'place_id': 1, 'code': '013141', 'fn': '013141-何文丰.pdf'}, {'place_id': 1, 'code': '015635', 'fn': '015635-王宇光.pdf'}, {'place_id': 1, 'code': '016224', 'fn': '016224-方丽华.pdf'}, {'place_id': 1, 'code': '014081', 'fn': '014081-谢希杭.pdf'}, {'place_id': 1, 'code': '019323', 'fn': '019323-赖佳奇.pdf'}, {'place_id': 1, 'code': '020747', 'fn': '020747-贺海鹏.pdf'}, {'place_id': 1, 'code': '014609', 'fn': '014609-靳贤锐.pdf'}, {'place_id': 1, 'code': '016309', 'fn': '016309-张鹏宇.pdf'}, {'place_id': 1, 'code': '015206', 'fn': '015206-王贺永.pdf'}, {'place_id': 1, 'code': '015184', 'fn': '015184-彭志涛.pdf'}, {'place_id': 1, 'code': '018706', 'fn': '018706-陈佳欣.pdf'}, {'place_id': 1, 'code': '021568', 'fn': '021568-张峻哲.pdf'}, {'place_id': 1, 'code': '016402', 'fn': '016402-石晓雨.pdf'}, {'place_id': 1, 'code': '016023', 'fn': '016023-何正楠.pdf'}, {'place_id': 1, 'code': '008319', 'fn': '008319-陈文近.pdf'}, {'place_id': 1, 'code': '014701', 'fn': '014701-陈顺.pdf'}, {'place_id': 1, 'code': '013564', 'fn': '013564-徐凯华.pdf'}, {'place_id': 1, 'code': '015014', 'fn': '015014-赵刚.pdf'}, {'place_id': 1, 'code': '010481', 'fn': '010481-徐旭东.pdf'}, {'place_id': 1, 'code': '016354', 'fn': '016354-张婕.pdf'}]\n"
]
}
],
"source": [
"\n",
"import os,sys,shutil\n",
"import json\n",
"import math\n",
"import glob\n",
"import random\n",
"from pathlib import Path\n",
"import pymongo\n",
"\n",
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
"mydb = myclient[\"baogao\"]\n",
"\n",
"place_id = 1\n",
"place_code = \"20\"\n",
"\n",
"#fi_path = '/root/data/flask/pdf/files'\n",
"#fi_path = '/home/songyi/python/mycrm/flask/pdf/files'\n",
"fls = glob.glob(f'{fi_path}/{str(place_id)}/*.pdf')\n",
"\n",
"list2 = []\n",
"for fn in fls:\n",
" dict2 = {}\n",
" fi_name =Path(fn).stem.split('-')[0]\n",
" #fi_name =Path(fn).stem\n",
" code = fi_name\n",
" dict2 = {'place_id':place_id,'code':code,'fn':Path(fn).name}\n",
" list2.append(dict2)\n",
" i +=1\n",
"x = mycol.insert_many(list2)\n",
"print(len(list2),'ok') "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c0380a6e-fdfe-4df1-b235-652e605ac312",
"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
}