674 lines
74 KiB
Plaintext
674 lines
74 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "4c74893b-fca2-45f8-8254-2060886909ec",
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"metadata": {},
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"source": [
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"## 人员信息导入"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e5472692-ffc3-442f-9b84-170619215148",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import openpyxl\n",
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"import json\n",
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"\n",
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"\n",
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"wb = openpyxl.load_workbook('data/积家人员信息.xlsx')\n",
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"sheet = wb.active\n",
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"# sheets = wb.sheetnames\n",
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"person = {}\n",
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"\n",
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"for n in range(2, sheet.max_row+1):\n",
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" code = int(sheet.cell(n, 1).value)\n",
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" person.setdefault(code, {})\n",
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" dict1 = {}\n",
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" dict1['name'] = sheet.cell(n, 2).value \n",
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" dict1['sex'] = sheet.cell(n, 3).value\n",
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" dict1['birth'] = str(sheet.cell(n,4).value).split(' ')[0]\n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['门牌号e'] = sheet.cell(n,6).value\n",
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" \n",
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" person[code] = dict1\n",
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"filename = 'data/积家人员信息.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(person, fl, ensure_ascii=False)\n",
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"print('ok')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0dc90cf8-0a51-49ab-8f93-81acfd359e63",
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"metadata": {},
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"source": [
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"## 获取人员测试成绩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "693820f4-f79d-4e6b-9901-0aae57bc6c92",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import datetime\n",
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"import csv\n",
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"from datetime import date\n",
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"\n",
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"filename = '../item.json'\n",
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"item = {}\n",
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"unit = {}\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"for k,v in dict1.items():\n",
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" item[k] = v\n",
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"item['1']['en'] = 'lung'\n",
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"item['2']['en'] = 'grip'\n",
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"item['3']['en'] = 'flexion'\n",
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"item['4']['en'] = 'jump'\n",
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"item['5']['en'] = 'pushup'\n",
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"item['6']['en'] = 'balance'\n",
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"item['7']['en'] = 'reaction'\n",
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"item['8']['en'] = 'step'\n",
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"item['9']['en'] = 'situp'\n",
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"item['10']['en'] = 'height'\n",
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"item['11']['en'] = 'weight'\n",
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"\n",
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"\n",
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"re_ta = {}\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"filename = 'data/积家人员信息.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"\n",
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"filename = 'data/places_result_20231103.csv'\n",
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
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" for line in fl:\n",
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" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
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" list1.append(line)\n",
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"#f_item = ['lung','grip','flexion','jump','balance','reaction','step','situp']\n",
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"#m_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
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"for result in list1:\n",
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" user = str(result[2])\n",
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" rq = date.fromisoformat(result[6].replace('/','-'))\n",
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" if user in dict1.keys():\n",
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" l_xm = []\n",
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" m_item = str(result[3]) \n",
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" re_ta.setdefault(user,{}) \n",
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" re_ta[user]['name'] = dict1[user]['name']\n",
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" re_ta[user]['sex'] = dict1[user]['sex']\n",
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" if dict1[user]['sex'] == '男':\n",
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" l_xm = ['weight','height','lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
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" else:\n",
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" l_xm = ['weight','height','lung','grip','flexion','jump','balance','reaction','step','situp']\n",
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" \n",
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" birth = date.fromisoformat(dict1[user]['birth'].replace('/','-'))\n",
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" #nian = int(birth[0].strip())\n",
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" #yue = int(birth[1].strip())\n",
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" #ri = int(birth[2].strip())\n",
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" #print(k,nian,yue,ri)\n",
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" item_name = item[m_item]['en'] \n",
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" if item_name in l_xm: \n",
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" days = (rq-birth).days \n",
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" re_ta[user]['age'] = int(days/365)\n",
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" re_ta[user]['month'] = int(days/365*12)\n",
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" re_ta[user]['rq'] = result[8]\n",
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"\n",
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"\n",
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" re_ta[user].setdefault(item_name,{}) \n",
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" score = int(result[4])/item[m_item]['divisor'] \n",
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" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
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"print(len(re_ta))\n",
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"filename = 'data/result_积家.json'\n",
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"\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(re_ta, fl, ensure_ascii=False) \n",
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"print(len(re_ta))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8b6cffa9-bd17-431e-a0b1-5004d4cf4726",
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"metadata": {},
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"source": [
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"## 导出人员信息"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "15b3ca3b-ec36-4d1d-bbaf-040fed6e2687",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import openpyxl\n",
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"\n",
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"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",
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"#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",
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"\n",
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"filename = 'data/result_积家.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"\n",
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"filename = 'data/积家人员信息.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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" \n",
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"list1 = []\n",
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"for k, v in dict1.items():\n",
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" list2 = []\n",
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" list2.append(str(k).rjust(5,'0'))\n",
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" list2.append(v['name']) \n",
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" list2.append(v['rq']) \n",
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" list2.append(v['sex'])\n",
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" list1.append(list2)\n",
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"filename = 'data/积家参加测试人员信息.xlsx'\n",
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"wb = openpyxl.Workbook()\n",
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"sheet = wb.active\n",
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"#sheet.append(title)\n",
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"for row in list1:\n",
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" sheet.append(row)\n",
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" \n",
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"wb.save(filename)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2d417d9a-ca85-4c9f-8673-11f5f1033d1f",
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"metadata": {},
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"source": [
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"## 计算项目成绩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9230c78a-40d1-47ed-9bfc-94525b44f8f9",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import time\n",
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"\n",
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"filename = '../item.json'\n",
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"item = {}\n",
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"unit = {}\n",
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"with open(filename,'r') as fl:\n",
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" dict3 = json.load(fl) \n",
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"for k,v in dict3.items():\n",
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" item[k] = v\n",
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"item['1']['en'] = 'lung'\n",
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"item['2']['en'] = 'grip'\n",
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"item['3']['en'] = 'flexion'\n",
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"item['4']['en'] = 'jump'\n",
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"item['5']['en'] = 'pushup'\n",
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"item['6']['en'] = 'balance'\n",
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"item['7']['en'] = 'reaction'\n",
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"item['8']['en'] = 'step'\n",
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"item['9']['en'] = 'situp'\n",
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"item['10']['en'] = 'height'\n",
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"item['11']['en'] = 'weight'\n",
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"\n",
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"filename = 'data/体质检测标准 (1).json' \n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"\n",
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"\n",
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"\n",
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"def cal_score(data1):\n",
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" #data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46} \n",
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" person = dict1['person']\n",
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" criteria = dict1['criteria']\n",
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" if data1['age'] >59:\n",
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" data1['age'] = 59\n",
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" if data1['age'] <20:\n",
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" data1['age'] = 20\n",
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" info = data1['sex']+str(data1['age'])\n",
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" bz = person[info]\n",
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" mx = criteria[bz][data1['item']]\n",
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" result = data1['result'] \n",
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" if data1['item'] == 'reaction':\n",
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" for bz1 in mx:\n",
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" if result > bz1:\n",
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" #print(bz1)\n",
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" score = mx.index(bz1,0)\n",
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" break\n",
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" else:\n",
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" score = 5\n",
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" else:\n",
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" for bz1 in mx:\n",
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" if result < bz1:\n",
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" #print(bz1)\n",
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" score = mx.index(bz1,0)\n",
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" break\n",
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" else:\n",
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" score = 5\n",
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" return(score)\n",
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"filename = 'data/体质检测标准_BMI.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict4 = json.load(fl) \n",
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" \n",
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"def cal_bmi(data1):\n",
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" # data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n",
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" person = dict4['person']\n",
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" criteria = dict4['criteria']\n",
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" if data1['age'] > 59:\n",
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" data1['age'] = 59\n",
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" if data1['age'] <20:\n",
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" data1['age'] = 20\n",
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" info = data1['sex']+str(data1['age'])\n",
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" bz = person[info]\n",
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" #print(bz)\n",
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" result = data1['result']\n",
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" #print(data1['code'],result)\n",
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" height = int(float(result.split(',')[0]))\n",
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" weight = float(result.split(',')[1])\n",
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" if str(height) not in criteria[bz]:\n",
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" score = 1\n",
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" else: \n",
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" mx = criteria[bz][str(height)]\n",
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" if weight < mx[0]:\n",
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" score = 1\n",
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" elif weight < mx[1]:\n",
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" score = 3\n",
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" elif weight < mx[2]:\n",
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" score = 5 \n",
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" elif weight <= mx[3]:\n",
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" score = 3 \n",
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" elif weight > mx[3]:\n",
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" score = 1\n",
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" return score\n",
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" \n",
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" \n",
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"\n",
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"#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
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"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
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"filename = 'data/result_积家.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl) \n",
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"for k, v in dict2.items():\n",
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" #print(k)\n",
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" if v['sex'] == '男':\n",
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" sex = 'M'\n",
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" else:\n",
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" sex = 'F' \n",
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" if 'height' in v.keys() and 'weight' in v.keys():\n",
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" bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
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" data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n",
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" dict2[k]['bmi'] = {}\n",
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" dict2[k]['bmi']['成绩'] = bmi_data\n",
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" dict2[k]['bmi']['score'] = cal_bmi(data1)\n",
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" for item_en in list_item:\n",
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" if item_en in v.keys(): \n",
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" data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n",
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" dict2[k][item_en]['score'] = cal_score(data1)\n",
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" #print(k,v[item_en]['成绩'],cal_score(data1))\n",
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"\n",
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"filename = f'data/result_积家.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict2,fl , ensure_ascii=False) \n",
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"print('ok!') "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4365fd0d-1e79-48a3-b580-3041a1340815",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "e86acc03-06e2-4eaf-8207-e1ba834869d3",
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"metadata": {},
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"source": [
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"## 问卷信息导入"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c42bb7f4-ae16-4950-8fc9-97e7084e4615",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import openpyxl\n",
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"import json\n",
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"\n",
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"filename = 'data/积家人员信息.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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"wb = openpyxl.load_workbook('data/积家问卷.xlsx')\n",
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"sheet = wb.active\n",
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"# sheets = wb.sheetnames\n",
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"dict1 = {}\n",
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"dict3 = {}\n",
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"sheet = wb.active\n",
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"data1 =list(sheet.values)\n",
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"list_bh = data1[0][1:]\n",
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"\n",
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"del data1[0]\n",
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"for i in range(1,len(list_bh)+1):\n",
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" list2 = []\n",
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" \n",
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" for item in data1:\n",
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" list2.append(item[i])\n",
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" dict1[list_bh[i-1]] = list2\n",
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"print(dict1)\n",
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"filename = 'data/result_积家.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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"for k,v in dict1.items():\n",
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" if str(k) in dict2.keys(): \n",
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" if v[0] is not None:\n",
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" psy_yangmiao_old = v[:30]\n",
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" dict2[str(k)]['psy'] = psy_yangmiao_old\n",
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" #dict2[str(k)]['psy_yangmiao_old'] = psy_yangmiao_old\n",
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" if v[30] is not None:\n",
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" tcm = v[30:90]\n",
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" dict2[str(k)]['tcm'] = tcm\n",
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" #print(tcm,len(tcm))\n",
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" if v[90] is not None:\n",
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" spine = v[90:116]\n",
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" xx22 = spine[21]\n",
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" xx23 = spine[22]\n",
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" spine[21] = xx23\n",
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" spine[22] = xx22\n",
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" dict2[str(k)]['spine'] = spine\n",
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" \n",
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" #dict2[str(k)]['psy'] = psy_yangmiao_old\n",
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" #dict2[str(k)]['tcm'] = tcm\n",
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" #dict2[str(k)]['spine'] = spine\n",
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"filename = 'data/result_积家1.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(dict2, fl, ensure_ascii=False) \n",
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"print('ok') "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c4ba35f4-1591-4f8e-8c19-8ff9bf918748",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
|
|
"id": "8ff5f29b-f2cd-4b2f-9716-8ec6bd77db1f",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 生成报告人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6038af14-e3cf-4e79-9a02-a5d70cb2ed65",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"filename = 'data/世纪花园人员信息.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"\n",
|
|
"list1 = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" id = str(k).rjust(5,\"0\")\n",
|
|
" \n",
|
|
" name = v['name']\n",
|
|
" list1.append([id,name,v['sex'],v['sex'],v['birth'],v['phone'],v['unit']])\n",
|
|
"filename = 'data/世纪花园人员信息.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": "e790c586-9099-4a63-a460-a6d53a1e8f99",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入问卷人员信息（有姓名）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "096672ef-c1f1-4b31-a490-efd408b95aec",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import datetime\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"list1 = []\n",
|
|
"filename = 'data/Survey_20231027.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",
|
|
"list3 = []\n",
|
|
"for item in list1:\n",
|
|
" phone = item[2]\n",
|
|
" content = json.loads(item[5])\n",
|
|
" name = content['name']\n",
|
|
" sex = content['gender']\n",
|
|
" birth = content['birth']\n",
|
|
" unit = content['unit']\n",
|
|
" list2 = [phone,name,sex,birth,unit]\n",
|
|
" list3.append(list2)\n",
|
|
"filename = 'data/世纪花园人员信息1.xlsx'\n",
|
|
"wb = openpyxl.Workbook()\n",
|
|
"sheet = wb.active\n",
|
|
"\n",
|
|
"for row in list3:\n",
|
|
" sheet.append(row)\n",
|
|
"wb.save(filename) \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5ab7d644-c90a-4877-9abf-6d4bd88ef3ef",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入问卷人员信息（无姓名）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "8f801647-a326-4bf1-a651-4b52e0296998",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"import json\n",
|
|
"\n",
|
|
"filename = 'data/世纪花园人员信息.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
" \n",
|
|
"list1 = []\n",
|
|
"list2 = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" list2.append(v['phone'])\n",
|
|
"print(list2)\n",
|
|
"\n",
|
|
"filename = 'data/Survey_20231027.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",
|
|
" phone = str(line[2])\n",
|
|
" if phone in list2:\n",
|
|
" print(phone)\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3e5b5d43-c883-4e41-80b6-dd80bdbfcbfa",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 问卷导出"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 38,
|
|
"id": "fbe793e4-04cf-4e7d-8fb8-1776ed474ab9",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-11-10T04:50:35.767483Z",
|
|
"iopub.status.busy": "2023-11-10T04:50:35.767191Z",
|
|
"iopub.status.idle": "2023-11-10T04:50:35.978054Z",
|
|
"shell.execute_reply": "2023-11-10T04:50:35.977514Z",
|
|
"shell.execute_reply.started": "2023-11-10T04:50:35.767458Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"('ptv_0533_jj','段玉华','953','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":3,\"q2O\":3,\"q3O\":4,\"q4O\":1,\"q5O\":4,\"q6O\":4,\"q7O\":4,\"q8O\":4,\"q9O\":5,\"q10O\":1,\"q11O\":3,\"q12O\":4,\"q13O\":4,\"q14O\":4,\"q15O\":4,\"q16O\":5,\"q17O\":5,\"q18O\":4,\"q19O\":3,\"q20O\":4,\"q21O\":3,\"q22O\":4,\"q23O\":5,\"q24O\":5,\"q25O\":4,\"q26O\":4,\"q27O\":3,\"q28O\":3,\"q29O\":3,\"q30O\":3,\"q1\":3,\"q3\":2,\"q4\":1,\"q5\":3,\"q6\":3,\"q8\":3,\"q10\":3,\"q13\":4,\"q14\":3,\"q15\":3,\"q16\":2,\"q17\":2,\"q18\":2,\"q19\":2,\"q20\":1,\"q22\":2,\"q23\":3,\"q25\":2,\"q26\":2,\"q27\":2,\"q28\":2,\"q29\":2,\"q30\":3,\"q31\":2,\"q32\":2,\"q33\":2,\"q34\":2,\"q35\":3,\"q36\":2,\"q37\":1,\"q38\":2,\"q39\":3,\"q40\":2,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":3,\"q45\":3,\"q46\":3,\"q47\":3,\"q48\":3,\"q49\":2,\"q50\":3,\"q51\":1,\"q52\":3,\"q53\":1,\"q54\":3,\"q55\":1,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":1,\"qv2\":2,\"qv3\":1,\"qv4\":1,\"qv5\":2,\"qv6\":2,\"qv7\":1,\"qv8\":1,\"qv9\":2,\"qv10\":2,\"qv11\":2,\"qv12\":1,\"qv13\":2,\"qv14\":2,\"qv15\":1,\"qv16\":1,\"qv17\":2,\"qv18\":1,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":1,\"qv25\":1,\"qv26\":2}','2023-11-10 12:00:00'),('ptv_0533_jj','孙俊英','329','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":1,\"q2O\":1,\"q3O\":1,\"q4O\":1,\"q5O\":5,\"q6O\":5,\"q7O\":5,\"q8O\":5,\"q9O\":5,\"q10O\":1,\"q11O\":5,\"q12O\":5,\"q13O\":5,\"q14O\":5,\"q15O\":5,\"q16O\":5,\"q17O\":5,\"q18O\":1,\"q19O\":4,\"q20O\":5,\"q21O\":5,\"q22O\":5,\"q23O\":5,\"q24O\":5,\"q25O\":5,\"q26O\":4,\"q27O\":4,\"q28O\":2,\"q29O\":4,\"q30O\":5,\"q1\":5,\"q3\":1,\"q4\":3,\"q5\":1,\"q6\":4,\"q8\":4,\"q10\":3,\"q13\":1,\"q14\":3,\"q15\":1,\"q16\":1,\"q17\":3,\"q18\":1,\"q19\":1,\"q20\":1,\"q22\":1,\"q23\":1,\"q25\":1,\"q26\":1,\"q27\":1,\"q28\":1,\"q29\":1,\"q30\":1,\"q31\":1,\"q32\":1,\"q33\":1,\"q34\":1,\"q35\":1,\"q36\":1,\"q37\":1,\"q38\":1,\"q39\":1,\"q40\":1,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":3,\"q45\":3,\"q46\":1,\"q47\":1,\"q48\":3,\"q49\":1,\"q50\":2,\"q51\":3,\"q52\":1,\"q53\":1,\"q54\":1,\"q55\":3,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":2,\"qv2\":2,\"qv3\":2,\"qv4\":2,\"qv5\":2,\"qv6\":2,\"qv7\":1,\"qv8\":2,\"qv9\":2,\"qv10\":2,\"qv11\":2,\"qv12\":2,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":2,\"qv17\":2,\"qv18\":1,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":2,\"qv25\":2,\"qv26\":2}','2023-11-10 12:00:00'),('ptv_0533_jj','赵兰芬','1125','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":4,\"q2O\":4,\"q3O\":2,\"q4O\":1,\"q5O\":4,\"q6O\":4,\"q7O\":4,\"q8O\":3,\"q9O\":5,\"q10O\":2,\"q11O\":4,\"q12O\":5,\"q13O\":5,\"q14O\":5,\"q15O\":5,\"q16O\":4,\"q17O\":4,\"q18O\":3,\"q19O\":4,\"q20O\":4,\"q21O\":4,\"q22O\":4,\"q23O\":4,\"q24O\":4,\"q25O\":5,\"q26O\":5,\"q27O\":4,\"q28O\":2,\"q29O\":4,\"q30O\":3,\"q1\":3,\"q3\":2,\"q4\":3,\"q5\":2,\"q6\":4,\"q8\":4,\"q10\":3,\"q13\":1,\"q14\":3,\"q15\":2,\"q16\":3,\"q17\":1,\"q18\":1,\"q19\":1,\"q20\":1,\"q22\":4,\"q23\":1,\"q25\":1,\"q26\":3,\"q27\":4,\"q28\":3,\"q29\":3,\"q30\":4,\"q31\":2,\"q32\":4,\"q33\":4,\"q34\":3,\"q35\":4,\"q36\":3,\"q37\":2,\"q38\":4,\"q39\":3,\"q40\":3,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":4,\"q45\":3,\"q46\":4,\"q47\":4,\"q48\":1,\"q49\":3,\"q50\":1,\"q51\":1,\"q52\":3,\"q53\":3,\"q54\":1,\"q55\":1,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":2,\"qv1\":1,\"qv2\":2,\"qv3\":2,\"qv4\":1,\"qv5\":2,\"qv6\":2,\"qv7\":1,\"qv8\":1,\"qv9\":1,\"qv10\":2,\"qv11\":1,\"qv12\":2,\"qv13\":1,\"qv14\":2,\"qv15\":1,\"qv16\":1,\"qv17\":2,\"qv18\":1,\"qv19\":2,\"qv20\":2,\"qv21\":1,\"qv22\":1,\"qv23\":2,\"qv24\":1,\"qv25\":2,\"qv26\":1}','2023-11-10 12:00:00'),('ptv_0533_jj','王翠华','1608','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":1,\"q2O\":1,\"q3O\":1,\"q4O\":1,\"q5O\":5,\"q6O\":5,\"q7O\":5,\"q8O\":5,\"q9O\":5,\"q10O\":1,\"q11O\":5,\"q12O\":5,\"q13O\":5,\"q14O\":5,\"q15O\":5,\"q16O\":5,\"q17O\":5,\"q18O\":1,\"q19O\":3,\"q20O\":5,\"q21O\":5,\"q22O\":5,\"q23O\":5,\"q24O\":5,\"q25O\":5,\"q26O\":4,\"q27O\":4,\"q28O\":2,\"q29O\":4,\"q30O\":5,\"q1\":5,\"q3\":1,\"q4\":3,\"q5\":1,\"q6\":4,\"q8\":4,\"q10\":1,\"q13\":1,\"q14\":1,\"q15\":1,\"q16\":1,\"q17\":3,\"q18\":1,\"q19\":1,\"q20\":1,\"q22\":1,\"q23\":1,\"q25\":1,\"q26\":1,\"q27\":1,\"q28\":1,\"q29\":1,\"q30\":1,\"q31\":1,\"q32\":1,\"q33\":1,\"q34\":1,\"q35\":1,\"q36\":1,\"q37\":1,\"q38\":1,\"q39\":1,\"q40\":1,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":3,\"q45\":3,\"q46\":1,\"q47\":1,\"q48\":3,\"q49\":1,\"q50\":2,\"q51\":3,\"q52\":1,\"q53\":1,\"q54\":3,\"q55\":5,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":2,\"qv2\":2,\"qv3\":2,\"qv4\":2,\"qv5\":2,\"qv6\":2,\"qv7\":1,\"qv8\":2,\"qv9\":2,\"qv10\":2,\"qv11\":2,\"qv12\":2,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":2,\"qv17\":2,\"qv18\":1,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":2,\"qv25\":2,\"qv26\":2}','2023-11-10 12:00:00'),('ptv_0533_jj','胡桂香','547','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":3,\"q2O\":1,\"q3O\":1,\"q4O\":1,\"q5O\":5,\"q6O\":5,\"q7O\":5,\"q8O\":5,\"q9O\":5,\"q10O\":1,\"q11O\":4,\"q12O\":5,\"q13O\":5,\"q14O\":5,\"q15O\":5,\"q16O\":5,\"q17O\":5,\"q18O\":5,\"q19O\":5,\"q20O\":4,\"q21O\":4,\"q22O\":5,\"q23O\":5,\"q24O\":5,\"q25O\":4,\"q26O\":4,\"q27O\":3,\"q28O\":2,\"q29O\":4,\"q30O\":4,\"q1\":4,\"q3\":1,\"q4\":2,\"q5\":3,\"q6\":3,\"q8\":3,\"q10\":3,\"q13\":1,\"q14\":3,\"q15\":3,\"q16\":3,\"q17\":3,\"q18\":4,\"q19\":1,\"q20\":1,\"q22\":4,\"q23\":1,\"q25\":1,\"q26\":3,\"q27\":2,\"q28\":1,\"q29\":3,\"q30\":3,\"q31\":1,\"q32\":3,\"q33\":1,\"q34\":1,\"q35\":1,\"q36\":1,\"q37\":1,\"q38\":3,\"q39\":1,\"q40\":1,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":1,\"q45\":1,\"q46\":1,\"q47\":2,\"q48\":3,\"q49\":3,\"q50\":4,\"q51\":1,\"q52\":4,\"q53\":1,\"q54\":4,\"q55\":3,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":2,\"qv1\":2,\"qv2\":2,\"qv3\":2,\"qv4\":2,\"qv5\":1,\"qv6\":2,\"qv7\":1,\"qv8\":1,\"qv9\":1,\"qv10\":2,\"qv11\":2,\"qv12\":1,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":2,\"qv17\":2,\"qv18\":2,\"qv19\":1,\"qv20\":2,\"qv21\":1,\"qv22\":2,\"qv23\":2,\"qv24\":1,\"qv25\":2,\"qv26\":2}','2023-11-10 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12:00:00'),('ptv_0533_jj','朱玉莲','1225','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":4,\"q2O\":3,\"q3O\":3,\"q4O\":2,\"q5O\":2,\"q6O\":3,\"q7O\":4,\"q8O\":3,\"q9O\":4,\"q10O\":3,\"q11O\":2,\"q12O\":4,\"q13O\":4,\"q14O\":4,\"q15O\":5,\"q16O\":4,\"q17O\":4,\"q18O\":4,\"q19O\":4,\"q20O\":3,\"q21O\":3,\"q22O\":4,\"q23O\":4,\"q24O\":4,\"q25O\":3,\"q26O\":3,\"q27O\":3,\"q28O\":3,\"q29O\":4,\"q30O\":3,\"q1\":3,\"q3\":4,\"q4\":3,\"q5\":4,\"q6\":3,\"q8\":4,\"q10\":3,\"q13\":3,\"q14\":2,\"q15\":4,\"q16\":3,\"q17\":4,\"q18\":4,\"q19\":4,\"q20\":2,\"q22\":3,\"q23\":2,\"q25\":2,\"q26\":4,\"q27\":3,\"q28\":3,\"q29\":3,\"q30\":4,\"q31\":2,\"q32\":2,\"q33\":1,\"q34\":2,\"q35\":4,\"q36\":2,\"q37\":1,\"q38\":2,\"q39\":3,\"q40\":4,\"q41\":1,\"q42\":2,\"q43\":2,\"q44\":4,\"q45\":4,\"q46\":3,\"q47\":4,\"q48\":3,\"q49\":3,\"q50\":4,\"q51\":1,\"q52\":3,\"q53\":1,\"q54\":3,\"q55\":5,\"q56\":3,\"q57\":2,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":2,\"qv2\":2,\"qv3\":2,\"qv4\":1,\"qv5\":2,\"qv6\":2,\"qv7\":1,\"qv8\":1,\"qv9\":1,\"qv10\":2,\"qv11\":1,\"qv12\":1,\"qv13\":2,\"qv14\":2,\"qv15\":1,\"qv16\":2,\"qv17\":2,\"qv18\":1,\"qv19\":1,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":1,\"qv25\":1,\"qv26\":2}','2023-11-10 12:00:00'),('ptv_0533_jj','张月华','190','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":3,\"q2O\":4,\"q3O\":3,\"q4O\":1,\"q5O\":3,\"q6O\":3,\"q7O\":3,\"q8O\":3,\"q9O\":3,\"q10O\":1,\"q11O\":3,\"q12O\":3,\"q13O\":3,\"q14O\":3,\"q15O\":4,\"q16O\":5,\"q17O\":5,\"q18O\":5,\"q19O\":3,\"q20O\":3,\"q21O\":3,\"q22O\":5,\"q23O\":3,\"q24O\":4,\"q25O\":3,\"q26O\":3,\"q27O\":3,\"q28O\":4,\"q29O\":4,\"q30O\":4,\"q1\":3,\"q3\":3,\"q4\":1,\"q5\":1,\"q6\":4,\"q8\":3,\"q10\":1,\"q13\":2,\"q14\":1,\"q15\":1,\"q16\":1,\"q17\":2,\"q18\":1,\"q19\":1,\"q20\":1,\"q22\":1,\"q23\":4,\"q25\":1,\"q26\":3,\"q27\":3,\"q28\":3,\"q29\":1,\"q30\":4,\"q31\":1,\"q32\":4,\"q33\":1,\"q34\":1,\"q35\":4,\"q36\":3,\"q37\":1,\"q38\":1,\"q39\":3,\"q40\":3,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":4,\"q45\":4,\"q46\":2,\"q47\":1,\"q48\":2,\"q49\":1,\"q50\":1,\"q51\":2,\"q52\":1,\"q53\":1,\"q54\":2,\"q55\":2,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":2,\"qv2\":2,\"qv3\":1,\"qv4\":1,\"qv5\":2,\"qv6\":2,\"qv7\":2,\"qv8\":2,\"qv9\":1,\"qv10\":2,\"qv11\":2,\"qv12\":2,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":1,\"qv17\":2,\"qv18\":2,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":1,\"qv23\":2,\"qv24\":2,\"qv25\":2,\"qv26\":2}','2023-11-10 12:00:00'),('ptv_0533_jj','朱训才','1117','{\"Gender\":\"m\",\"Age\":\"O\",\"q1O\":1,\"q2O\":1,\"q3O\":1,\"q4O\":1,\"q5O\":5,\"q6O\":5,\"q7O\":5,\"q8O\":5,\"q9O\":5,\"q10O\":1,\"q11O\":5,\"q12O\":5,\"q13O\":5,\"q14O\":5,\"q15O\":5,\"q16O\":5,\"q17O\":5,\"q18O\":4,\"q19O\":5,\"q20O\":5,\"q21O\":5,\"q22O\":5,\"q23O\":5,\"q24O\":5,\"q25O\":5,\"q26O\":5,\"q27O\":5,\"q28O\":4,\"q29O\":5,\"q30O\":5,\"q1\":5,\"q3\":1,\"q4\":1,\"q5\":1,\"q6\":1,\"q8\":4,\"q10\":1,\"q13\":1,\"q14\":1,\"q15\":1,\"q16\":1,\"q17\":1,\"q18\":3,\"q19\":3,\"q20\":1,\"q22\":1,\"q23\":1,\"q25\":2,\"q26\":1,\"q27\":1,\"q28\":1,\"q29\":1,\"q30\":1,\"q31\":1,\"q32\":1,\"q33\":1,\"q34\":1,\"q35\":2,\"q36\":1,\"q37\":1,\"q38\":1,\"q39\":3,\"q40\":1,\"q41\":1,\"q42\":1,\"q43\":2,\"q44\":1,\"q45\":3,\"q46\":1,\"q47\":2,\"q48\":1,\"q49\":1,\"q50\":1,\"q51\":1,\"q52\":3,\"q53\":1,\"q54\":3,\"q55\":1,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":1,\"qv2\":2,\"qv3\":1,\"qv4\":2,\"qv5\":2,\"qv6\":2,\"qv7\":2,\"qv8\":2,\"qv9\":2,\"qv10\":2,\"qv11\":2,\"qv12\":2,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":2,\"qv17\":2,\"qv18\":2,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":2,\"qv25\":2,\"qv26\":1}','2023-11-10 12:00:00'),('ptv_0533_jj','荣翠英','864','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":3,\"q2O\":4,\"q3O\":2,\"q4O\":1,\"q5O\":3,\"q6O\":3,\"q7O\":4,\"q8O\":4,\"q9O\":4,\"q10O\":1,\"q11O\":4,\"q12O\":4,\"q13O\":4,\"q14O\":4,\"q15O\":5,\"q16O\":4,\"q17O\":4,\"q18O\":4,\"q19O\":3,\"q20O\":3,\"q21O\":4,\"q22O\":4,\"q23O\":4,\"q24O\":4,\"q25O\":3,\"q26O\":3,\"q27O\":3,\"q28O\":4,\"q29O\":4,\"q30O\":3,\"q1\":3,\"q3\":2,\"q4\":2,\"q5\":4,\"q6\":3,\"q8\":4,\"q10\":2,\"q13\":2,\"q14\":2,\"q15\":4,\"q16\":4,\"q17\":3,\"q18\":4,\"q19\":4,\"q20\":2,\"q22\":2,\"q23\":2,\"q25\":1,\"q26\":1,\"q27\":1,\"q28\":1,\"q29\":1,\"q30\":4,\"q31\":2,\"q32\":2,\"q33\":1,\"q34\":1,\"q35\":4,\"q36\":3,\"q37\":1,\"q38\":1,\"q39\":1,\"q40\":2,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":3,\"q45\":3,\"q46\":3,\"q47\":4,\"q48\":1,\"q49\":2,\"q50\":1,\"q51\":1,\"q52\":2,\"q53\":1,\"q54\":1,\"q55\":1,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":3,\"qv1\":2,\"qv2\":2,\"qv3\":2,\"qv4\":1,\"qv5\":2,\"qv6\":2,\"qv7\":2,\"qv8\":1,\"qv9\":2,\"qv10\":2,\"qv11\":2,\"qv12\":2,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":2,\"qv17\":2,\"qv18\":1,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":1,\"qv25\":2,\"qv26\":2}','2023-11-10 12:00:00'),('ptv_0533_jj','刘玉云','675','{\"Gender\":\"f\",\"Age\":\"O\",\"q1O\":3,\"q2O\":2,\"q3O\":2,\"q4O\":1,\"q5O\":3,\"q6O\":3,\"q7O\":4,\"q8O\":4,\"q9O\":4,\"q10O\":1,\"q11O\":3,\"q12O\":4,\"q13O\":4,\"q14O\":4,\"q15O\":5,\"q16O\":4,\"q17O\":4,\"q18O\":4,\"q19O\":3,\"q20O\":3,\"q21O\":4,\"q22O\":4,\"q23O\":4,\"q24O\":4,\"q25O\":4,\"q26O\":4,\"q27O\":3,\"q28O\":2,\"q29O\":4,\"q30O\":3,\"q1\":3,\"q3\":2,\"q4\":2,\"q5\":2,\"q6\":3,\"q8\":4,\"q10\":2,\"q13\":2,\"q14\":2,\"q15\":2,\"q16\":4,\"q17\":2,\"q18\":2,\"q19\":2,\"q20\":2,\"q22\":3,\"q23\":2,\"q25\":1,\"q26\":1,\"q27\":1,\"q28\":1,\"q29\":1,\"q30\":4,\"q31\":2,\"q32\":2,\"q33\":1,\"q34\":1,\"q35\":4,\"q36\":2,\"q37\":1,\"q38\":3,\"q39\":1,\"q40\":2,\"q41\":1,\"q42\":1,\"q43\":1,\"q44\":2,\"q45\":3,\"q46\":3,\"q47\":4,\"q48\":1,\"q49\":2,\"q50\":1,\"q51\":1,\"q52\":3,\"q53\":1,\"q54\":1,\"q55\":1,\"q56\":1,\"q57\":1,\"q58\":1,\"q59\":1,\"q60\":1,\"qv1\":2,\"qv2\":2,\"qv3\":2,\"qv4\":1,\"qv5\":2,\"qv6\":2,\"qv7\":1,\"qv8\":1,\"qv9\":2,\"qv10\":2,\"qv11\":2,\"qv12\":2,\"qv13\":2,\"qv14\":2,\"qv15\":2,\"qv16\":2,\"qv17\":2,\"qv18\":1,\"qv19\":2,\"qv20\":2,\"qv21\":2,\"qv22\":2,\"qv23\":2,\"qv24\":2,\"qv25\":2,\"qv26\":2}','2023-11-10 12:00:00'),\n",
|
|
"{'encoding': 'utf-8', 'confidence': 0.99, 'language': ''}\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"import json\n",
|
|
"import chardet\n",
|
|
"\n",
|
|
"filename = 'data/积家人员信息.json'\n",
|
|
"with open(filename,'r',encoding='utf8') as fl:\n",
|
|
" dict3 = json.load(fl)\n",
|
|
"wb = openpyxl.load_workbook('data/积家问卷.xlsx')\n",
|
|
"sheet = wb.active\n",
|
|
"# sheets = wb.sheetnames\n",
|
|
"dict1 = {}\n",
|
|
"zy = [2,7,9,11,12,21,24]\n",
|
|
"no_xinli = [286]\n",
|
|
"sheet = wb.active\n",
|
|
"data1 =list(sheet.values)\n",
|
|
"list_bh = data1[0][1:]\n",
|
|
"#print(list_bh)\n",
|
|
"del data1[0]\n",
|
|
"\n",
|
|
"for i in range(1,len(list_bh)+1):\n",
|
|
" list2 = []\n",
|
|
" \n",
|
|
" for item in data1:\n",
|
|
" list2.append(item[i])\n",
|
|
" dict1[list_bh[i-1]] = list2\n",
|
|
"#print(dict1)\n",
|
|
"s = ''\n",
|
|
"for k,v in dict1.items():\n",
|
|
" if str(k) in dict3.keys(): \n",
|
|
" if dict3[str(k)]['sex'] =='男':\n",
|
|
" sex = \"m\"\n",
|
|
" else:\n",
|
|
" sex = \"f\"\n",
|
|
" dict2 = {}\n",
|
|
" list_mx = []\n",
|
|
" list_mx.append(f'\"Gender\":\"{sex}\"')\n",
|
|
" list_mx.append(f'\"Age\":\"O\"')\n",
|
|
" dict2['surveyId'] = \"merge1\"\n",
|
|
" dict2['name'] = dict3[str(k)]['name'] \n",
|
|
" dict2['code'] = str(k) \n",
|
|
" name = dict3[str(k)]['name'] \n",
|
|
" if k not in no_xinli:\n",
|
|
" for i in range(0,30):\n",
|
|
" list_mx.append(f'\"q{i+1}O\":{v[i]}') \n",
|
|
" \n",
|
|
" for i in range(1,61):\n",
|
|
" if i not in zy:\n",
|
|
" list_mx.append(f'\"q{i}\":{v[29+i]}')\n",
|
|
" for i in range(1,27):\n",
|
|
" list_mx.append(f'\"qv{i}\":{v[89+i]}')\n",
|
|
" ss = ','.join(list_mx)\n",
|
|
" ss ='{'+ss+'}'\n",
|
|
" dict2['data'] = ss\n",
|
|
" sj = '2023-11-10 12:00:00'\n",
|
|
" \n",
|
|
" \n",
|
|
" s= s+f'(\\'ptv_0533_jj\\',\\'{name}\\',\\'{int(k)}\\',\\'{ss}\\',\\'{sj}\\'),'\n",
|
|
" #print(dict2)\n",
|
|
"print(s)\n",
|
|
"print (chardet.detect(str.encode(s)))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9a634c3b-6954-4eff-bc1c-3f5e229bc458",
|
|
"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": "3.10.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|