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{
"cells": [
{
"cell_type": "markdown",
"id": "1853a5ff-55c9-4c07-bc84-66e86b238fdc",
"metadata": {},
"source": [
"## 人员基本信息导入"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d6449ec6-54af-4f68-8c32-69372e390acf",
"metadata": {
"execution": {
"iopub.execute_input": "2025-09-22T03:30:37.564857Z",
"iopub.status.busy": "2025-09-22T03:30:37.564250Z",
"iopub.status.idle": "2025-09-22T03:30:37.781384Z",
"shell.execute_reply": "2025-09-22T03:30:37.780531Z",
"shell.execute_reply.started": "2025-09-22T03:30:37.564798Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"33 ok\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"\n",
"\n",
"wb = openpyxl.load_workbook('data/通用技术中国医药人员信息.xlsx',data_only=True)\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, 5).value\n",
" dict1['unit'] = sheet.cell(n, 4).value \n",
" dict1['birth'] = str(sheet.cell(n, 3).value).replace('/','-').split(' ')[0]\n",
" dict1['phone'] = sheet.cell(n, 5).value \n",
" person[code] = dict1\n",
"filename = 'data/通用技术中国医药人员.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": "7b114094-afdc-4776-8fb7-19ac05162e68",
"metadata": {},
"source": [
"## 导入手工数据"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c24c957e-6cc5-4cab-81e2-cec86a7498c7",
"metadata": {
"execution": {
"iopub.execute_input": "2025-09-22T03:48:21.444109Z",
"iopub.status.busy": "2025-09-22T03:48:21.443422Z",
"iopub.status.idle": "2025-09-22T03:48:21.472961Z",
"shell.execute_reply": "2025-09-22T03:48:21.472454Z",
"shell.execute_reply.started": "2025-09-22T03:48:21.444045Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"33\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"import time\n",
"from datetime import date\n",
"\n",
"wb = openpyxl.load_workbook('data/通用技术中国医药手工数据.xlsx',data_only=True)\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"\n",
"filename = 'data/通用技术中国医药人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"\n",
"dict2 = {}\n",
"\n",
"for n in range(2, sheet.max_row+1):\n",
" code = str(sheet.cell(n, 1).value)\n",
" rq = date.fromisoformat('2025-09-18')\n",
" birth = date.fromisoformat(dict1[code]['birth'].replace('/','-'))\n",
" dict2[code] = dict1[code]\n",
" days = (rq-birth).days\n",
" dict2[code]['age'] = int(days/365)\n",
" dict2[code]['month'] = int(days/365*12)\n",
" dict2[code]['rq'] = '2025-09-18'\n",
" if sheet.cell(n,4).value:\n",
" dict2[code].setdefault('reaction',{})\n",
" dict2[code]['reaction']['成绩'] = sheet.cell(n, 4).value\n",
" if sheet.cell(n,5).value:\n",
" dict2[code].setdefault('grip',{})\n",
" dict2[code]['grip']['成绩'] = sheet.cell(n, 5).value\n",
" if sheet.cell(n,7).value:\n",
" dict2[code].setdefault('lung',{})\n",
" dict2[code]['lung']['成绩'] = sheet.cell(n, 7).value\n",
" if sheet.cell(n,6).value:\n",
" dict2[code].setdefault('balance',{})\n",
" dict2[code]['balance']['成绩'] = sheet.cell(n, 6).value\n",
" if sheet.cell(n,3).value:\n",
" dict2[code].setdefault('bmi',{})\n",
" dict2[code]['bmi']['成绩'] = sheet.cell(n, 3).value\n",
"\n",
"\n",
"filename = 'data/result_通用技术中国医药.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl, ensure_ascii=False) \n",
"print(len(dict2))"
]
},
{
"cell_type": "markdown",
"id": "57aedeb8-02e6-47d2-a54a-e803d441104a",
"metadata": {},
"source": [
"## 生成测试得分"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a64ad6b7-b1dd-42ca-9619-3adcb8e0674e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "84ad4891-f424-417c-8818-c9544bff67ef",
"metadata": {},
"source": [
"## 导入问卷信息(新)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "020be101-938b-427e-918d-faf2e74b5b7e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-09-22T03:57:31.502714Z",
"iopub.status.busy": "2025-09-22T03:57:31.501987Z",
"iopub.status.idle": "2025-09-22T03:57:31.516781Z",
"shell.execute_reply": "2025-09-22T03:57:31.515780Z",
"shell.execute_reply.started": "2025-09-22T03:57:31.502649Z"
}
},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"import time\n",
"from datetime import date\n",
"\n",
"\n",
"\n",
"dict1 = {}\n",
"\n",
"filename = 'data/result_通用技术中国医药.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"filename = 'data/通用技术中国医药人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = json.load(fl)\n",
"\n",
"phone = {}\n",
"for k,v in dict3.items():\n",
" if 'phone' in v.keys():\n",
" phone[int(v['phone'])] = k\n",
"\n",
"list1 = []\n",
"filename = 'data/survey_records_20250922.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",
" list1.append(line)\n",
"\n",
"nn = 0\n",
"for item in list1:\n",
" if int(item[3]) in phone.keys(): \n",
" tcm = []\n",
" code = phone[int(item[3])]\n",
" \n",
" for i in range(0,60):\n",
" tcm.append(0)\n",
" \n",
" \n",
" content = json.loads(item[4])\n",
" if code not in dict1.keys():\n",
" dict1[code] = dict3[code]\n",
" rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
" dict1[code]['rq'] = str(date.fromisoformat(item[5].replace('/','-').split(' ')[0]))\n",
" #dict1[code]['rq'] = item[5].replace('/','-').split(' ')[0]\n",
" else:\n",
" rq=date.fromisoformat('2025-09-18')\n",
" dict1[code]['rq'] = '2025-09-18'\n",
" for k, v in content.items():\n",
" \n",
" if 'tcm' in k:\n",
" i = int(k[3:])\n",
" tcm[i-1] = int(v) \n",
" \n",
" if 'tcm' in item[4]: \n",
" dict1[code]['tcm'] = tcm\n",
" \n",
" birth = date.fromisoformat(dict3[code]['birth'].replace('/','-'))\n",
" \n",
" days = (rq-birth).days \n",
" dict1[code]['age'] = int(days/365)\n",
" dict1[code]['month'] = int(days/365*12)\n",
" #print(phone[item[2]])\n",
" nn+=1\n",
"filename = 'data/result_通用技术中国医药-1.json'\n",
"\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl, ensure_ascii=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9560d0ca-4d39-400b-b054-214e243ca4e5",
"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"
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"nbformat": 4,
"nbformat_minor": 5
}