1085 lines
32 KiB
Plaintext
1085 lines
32 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "70c15816-2ad5-4486-be33-378963d70934",
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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": "07f7e97e-670e-4301-b83d-1304514f15d5",
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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/xizang.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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" if sheet.cell(n,1).value is not None:\n",
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" code = int(sheet.cell(n, 5).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, 1).value\n",
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" if sheet.cell(n, 2).value ==0:\n",
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" sex = '男'\n",
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" else:\n",
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" sex = '女'\n",
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" dict1['sex'] = sex\n",
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" birth = str(sheet.cell(n, 3).value).split()[0]\n",
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" dict1['birth'] = birth\n",
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" \n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['phone'] = str(sheet.cell(n, 4).value) \n",
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" person[code] = dict1\n",
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"\n",
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"filename = 'data/西藏人员.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": "be805082-d5d7-405b-975c-fb902085a041",
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"metadata": {},
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"source": [
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"## 文件更名"
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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": "b51cf562-c708-4164-8431-5093247880c4",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os,sys,shutil\n",
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"import json\n",
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"import math\n",
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"import glob\n",
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"from pathlib import Path\n",
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"\n",
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"fi_path = 'file/2023-06-07'\n",
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"old = []\n",
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"dict2 = {}\n",
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"\n",
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"filename = 'data/西藏人员.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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"for k, v in dict1.items():\n",
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" m_name = v['name']\n",
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" dict2[int(k)] = [m_name]\n",
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"\n",
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"fls = glob.glob(f'{fi_path}/*.pdf')\n",
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"\n",
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"for fn in fls:\n",
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" old.append(os.path.basename(fn).split('.')[0])\n",
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"\n",
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"for n in old: \n",
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" o_name = f'{fi_path}/{n}.pdf'\n",
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" new_path = Path(fi_path,'new')\n",
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" new_path.mkdir(parents = True, exist_ok = True)\n",
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" n_name = Path(new_path,f'{str(n).rjust(5,\"0\")}-{dict2[int(n)][0]}.pdf')\n",
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" if not os.path.exists(n_name):\n",
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" shutil.copyfile(o_name,n_name)\n",
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" print(n_name)\n",
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" \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": "962f6edd-c8d1-42a2-aaff-58f92ccf8d56",
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"metadata": {},
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"source": [
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"## 问卷人员信息导入"
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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": "80d51661-e306-477a-84e8-8b9daf9cdb21",
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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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"import datetime\n",
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"\n",
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"wb = openpyxl.load_workbook('data/西藏健康体质检测人员名单.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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" if sheet.cell(n,7).value is not None and sheet.cell(n,4).value is not None:\n",
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" bh = int(sheet.cell(n, 7).value)\n",
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" person.setdefault(bh, {})\n",
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" dict1 = {}\n",
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" dict1['name'] = sheet.cell(n, 2).value\n",
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" dict1['code'] = sheet.cell(n, 1).value\n",
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" if sheet.cell(n, 3).value ==1:\n",
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" sex = '男'\n",
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" else:\n",
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" sex = '女'\n",
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" dict1['sex'] = sex\n",
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" birth = str(sheet.cell(n, 4).value).split()[0]\n",
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" \n",
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" if len(birth) == 2:\n",
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" dict1['age'] = int(birth)\n",
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" else:\n",
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" birth.replace('/','-')\n",
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" \n",
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" birth = birth.split('-') \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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" days = (datetime.date(2023, 5, 31)-datetime.date(nian,yue,ri)).days\n",
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" dict1['age'] = round(days/365)\n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['phone'] = str(sheet.cell(n, 5).value) \n",
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" person[bh] = dict1\n",
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"\n",
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"filename = 'data/西藏手工问卷人员名单.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": "25ffcc7a-5709-4377-b821-bce5097cbd78",
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"metadata": {},
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"source": [
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"## 导入脊柱问卷信息"
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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": "85599cf2-3673-4d3b-ae77-f5ef77217f71",
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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/西藏手工记录.xlsx')\n",
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"sheet = wb['Sheet1']\n",
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"\n",
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"dict1 = {}\n",
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"data1 =list(sheet.values)\n",
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"list_bh = data1[0][1:]\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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" dict1.setdefault(int(list_bh[i-1]),{})\n",
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" for item in data1:\n",
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" list2.append(item[i])\n",
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" dict1[int(list_bh[i-1])]['wenjuan'] = list2\n",
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"print(dict1)\n",
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"filename = 'data/西藏脊柱问卷原始信息.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(dict1, 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": "56538b71-aedc-4880-b655-a814778bda07",
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"metadata": {},
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"source": [
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"## 导入体测信息"
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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": "fa2fe417-cd1d-47c1-bcf6-2e711d49af20",
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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/西藏手工记录.xlsx')\n",
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"sheet = wb['Sheet2']\n",
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"filename = 'data/西藏脊柱问卷原始信息.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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"data1 =list(sheet.values)\n",
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"\n",
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"for item in data1:\n",
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" bh = str(item[0])\n",
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" dict1.setdefault(bh,{})\n",
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" xm = item[1]\n",
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" result = item[2]\n",
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" dict1[bh][xm] = result\n",
|
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"filename = 'data/西藏脊柱问卷原始信息.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(dict1, 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": "0a66d37f-6436-4e3c-abe1-d5fd4796e683",
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"metadata": {},
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"source": [
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"## 导出手工信息"
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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": "59b31b70-2af4-40ba-af8c-e72354508c19",
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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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"\n",
|
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"filename = 'data/西藏手工问卷人员名单.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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"filename = 'data/西藏脊柱问卷原始信息.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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"for k, v in dict1.items():\n",
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" s = ''\n",
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" if k in dict2.keys():\n",
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" if dict2[str(k)]['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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" dict3 = {}\n",
|
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" list_mx = []\n",
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" name = dict2[str(k)]['name'] \n",
|
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" list_mx.append(f'\"name\":\"{name}\"')\n",
|
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" list_mx.append(f'\"Gender\":\"{sex}\"')\n",
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" age = dict2[str(k)]['age']\n",
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" list_mx.append(f'\"Age\":{age}')\n",
|
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" dict3['surveyId'] = \"zsyxz1\"\n",
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" dict3['name'] = dict2[str(k)]['name'] \n",
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" code = dict2[str(k)]['code']\n",
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" for item in v.keys():\n",
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" if item == 'wenjuan':\n",
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" for i in range(0,21):\n",
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" if v[item][i] ==1:\n",
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" result = 'ture'\n",
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" else:\n",
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" result ='false' \n",
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" item_name = 'q'+str(i+1)\n",
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" list_mx.append(f'\"{item_name}\":{result}')\n",
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" for i in range(23,25):\n",
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" if v[item][i] ==1:\n",
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" result = 'ture'\n",
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" else:\n",
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" result ='false' \n",
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" item_name = 'q'+str(i)\n",
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" list_mx.append(f'\"{item_name}\":{result}')\n",
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" if sex == 'f':\n",
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" item_name = 'q25a'\n",
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" if v[item][21] ==1:\n",
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" result = 'ture'\n",
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" else:\n",
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" result ='false'\n",
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" list_mx.append(f'\"{item_name}\":{result}')\n",
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" else:\n",
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" item_name = 'q22'\n",
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" if v[item][22] ==1:\n",
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" result = 'ture'\n",
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" else:\n",
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" result ='false'\n",
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" list_mx.append(f'\"{item_name}\":{result}')\n",
|
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" item_name = 'q25b'\n",
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" if v[item][25] ==1:\n",
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" result = 'ture'\n",
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" else:\n",
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" result ='false'\n",
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" list_mx.append(f'\"{item_name}\":{result}')\n",
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" else: \n",
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" item_name = item \n",
|
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" list_mx.append(f'\"{item_name}\":{v[item]}')\n",
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" ss = ','.join(list_mx)\n",
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" ss ='{'+ss+'}'\n",
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" dict3['data'] = ss\n",
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" sj = '2023-06-01 20:00:00'\n",
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" s= s+f'(\"zsyxz1\",\"{name}\",\"{code}\",\\'{ss}\\',\"{sj}\"),'\n",
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" print(s)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3d7ab69c-941d-4f73-8708-2aab850ae2e1",
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"metadata": {},
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"source": [
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"## 导入体测信息"
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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": "e19a4c58-df1e-4136-bf10-33e9ed885e50",
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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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"import csv\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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"re_ta = {}\n",
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"dict1 = {}\n",
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"list1 = []\n",
|
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"filename = 'data/西藏人员.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_20230704.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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"#print(list1)\n",
|
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"for result in list1:\n",
|
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" user = str(result[2])\n",
|
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" if user in dict1.keys(): \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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" item_name = item[m_item]['name']\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",
|
|
"filename = 'data/result_xizang.json'\n",
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"\n",
|
|
"with open(filename,'w') as fl:\n",
|
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" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
|
"print(len(re_ta))"
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]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "52597677-83a0-447e-95b2-7e8c4296bec7",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 报告更名"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a84f2536-9e03-442f-8931-53c9fdc57395",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import math\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"\n",
|
|
"fi_path = 'file/2023-06-06'\n",
|
|
"old = []\n",
|
|
"dict2 = {}\n",
|
|
"\n",
|
|
"filename = 'data/result_xizang.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
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"\n",
|
|
"for k, v in dict1.items():\n",
|
|
" m_name = v['name']\n",
|
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" dict2[int(k)] = [m_name]\n",
|
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"\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
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"\n",
|
|
"for fn in fls:\n",
|
|
" old.append(os.path.basename(fn).split('.')[0])\n",
|
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"\n",
|
|
"for n in old: \n",
|
|
" o_name = f'{fi_path}/{n}.pdf'\n",
|
|
" new_path = Path(fi_path,'new')\n",
|
|
" new_path.mkdir(parents = True, exist_ok = True)\n",
|
|
" n_name = Path(new_path,f'{str(n).rjust(5,\"0\")}-{dict2[int(n)][0]}.pdf')\n",
|
|
" if not os.path.exists(n_name):\n",
|
|
" shutil.copyfile(o_name,n_name)\n",
|
|
" print(n_name)\n",
|
|
" \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "682c45e3-2e07-4fb0-844c-c837b1a2602c",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 数据分析"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "8c8faef4-c0d1-441e-ab64-3b8223afa3bd",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 获取清理后数据"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3696d7e1-afb8-4f9d-ba29-9aaa977b52de",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"item = {}\n",
|
|
"unit = {}\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" item[k] = v\n",
|
|
"filename = 'data/西藏人员.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"re_ta = {}\n",
|
|
"list1 = []\n",
|
|
"#print(\"\\n运动项目信息：\")\n",
|
|
"filename = 'data/places_result_20230714.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",
|
|
" \n",
|
|
" re_ta[user]['sex'] = dict1[user]['sex']\n",
|
|
" re_ta[user]['birth'] = dict1[user]['birth'].replace('-','/')\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",
|
|
" re_ta[user][item_name]['得分'] =result[5]\n",
|
|
"\n",
|
|
"print(len(re_ta))\n",
|
|
"liwai = []\n",
|
|
"for k, v in re_ta.items():\n",
|
|
" if (len(v)<8 and '身高' in v and '体重' in v) or (len(v)<7 and '身高' not in v and '体重' not in v) :\n",
|
|
" liwai.append(k)\n",
|
|
"print(liwai)\n",
|
|
"for k in liwai:\n",
|
|
" del re_ta[k]\n",
|
|
"print(len(re_ta))\n",
|
|
"filename = 'data/result_xizang.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(re_ta, fl) \n",
|
|
"print('ok')\n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "e9408f20-15cc-4827-bc34-f340f2e8b70f",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算人员年龄"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b71c8bf6-2530-425f-9516-8757b40e3dc5",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import datetime\n",
|
|
"\n",
|
|
"filename = 'data/result_xizang.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"for k, v in dict1.items(): \n",
|
|
" birth = v['birth'].split()[0].split('/') \n",
|
|
" nian = int(birth[0].strip())\n",
|
|
" yue = int(birth[1].strip())\n",
|
|
" ri = int(birth[2].strip())\n",
|
|
" #print(k,nian,yue,ri)\n",
|
|
" days = (datetime.date(2023, 6, 10)-datetime.date(nian,yue,ri)).days\n",
|
|
" v['age'] = int(days/365)\n",
|
|
"filename = 'data/result_xizang.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl) \n",
|
|
"print('ok') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "36461621-bd49-4eac-b055-9c421604d5fe",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 汇总人员信息及成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0e75cfbb-2b63-4163-831c-933fff1481c2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\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",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k,v in dict1.items():\n",
|
|
" score = 0\n",
|
|
" i = 0 \n",
|
|
" for k1,v1 in v.items(): \n",
|
|
" if k1 in items:\n",
|
|
" score = score + int(v1['得分'])\n",
|
|
" i+=1\n",
|
|
" dict1[k]['score'] = round(score/i,2) \n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "eb2b6efa-206a-4afe-8380-86970162b519",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算测试等级"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "99f02e37-3a03-4d7d-a2b9-7bf5563c253c",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\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",
|
|
"\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",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "386c1365-81e1-40a5-bcb1-c63b5ab7b52f",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 根据年龄汇总人员信息及成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1435c8af-094d-44b3-a024-af3615c07c21",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 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",
|
|
" \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": "0119fb2f-417d-4753-b3da-fac2be8546e3",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### 根据年龄汇总人员信息及成绩（男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "650cf1eb-8681-4911-9b04-80468fe6bf64",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"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：{round(score/i,2)}分，人数：{i}人')\n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：0人') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "9a7d06f0-32e4-4148-93f8-a81abfcd81a6",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### 根据年龄汇总人员信息及成绩（女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9ccb9b3c-de57-49f4-a4c6-10a24737e857",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\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：{round(score/i,2)}分，人数：{i}人')\n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：0人') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "90f534af-f370-4184-922a-a4a0444f59c3",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算平均成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c8cd897e-0d41-4faa-860f-395d42208674",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"#filename = 'data/result_石家庄.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/165,4)}分，总体：165人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c09369b2-0a21-4a61-b3c8-681906f74250",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各年龄段测试等级(女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "28b418f2-2324-450f-9684-4df15e012694",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"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": "40a7d9fb-cb74-4747-b6fe-9f8bc235d620",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各年龄段测试等级(男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a80224fb-1726-4370-9d3d-6e0a27afa8b2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"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": "7870236d-dc80-4c36-ab24-d880155d376b",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各项目成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "945b9bec-247b-498b-96f6-a52fabbf6c89",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"items = ['体重','肺活量','握力','坐位体前屈','单脚站立','选择反应时']\n",
|
|
"for item in items:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items():\n",
|
|
" if item in v.keys():\n",
|
|
" n = n + 1\n",
|
|
" score =score + int(v[item]['得分'])\n",
|
|
" print(item,round(score/n,2),n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "abba5b74-bfcd-4ec0-b682-10170138ff36",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 生成脊椎情况明细"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "da4ba403-92a8-4fd8-8dfc-49802b941fca",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"id": "aebb4eb4-2bcd-411c-8868-292fae38d8b5",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-07-19T05:21:21.489267Z",
|
|
"iopub.status.busy": "2023-07-19T05:21:21.488401Z",
|
|
"iopub.status.idle": "2023-07-19T05:21:21.503231Z",
|
|
"shell.execute_reply": "2023-07-19T05:21:21.502005Z",
|
|
"shell.execute_reply.started": "2023-07-19T05:21:21.489227Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"{'q1': 34, 'q2': 37, 'q3': 32, 'q4': 86, 'q5': 55, 'q6': 33, 'q7': 63, 'q8': 29, 'q9': 59, 'q10': 14, 'q11': 47, 'q12': 58, 'q13': 14, 'q14': 8, 'q15': 54, 'q16': 52, 'q17': 20, 'q18': 54, 'q19': 43, 'q20': 1, 'q21': 31, 'q22': 22, 'q23': 50, 'q24': 10, 'q25': 2}\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"dict1 = {}\n",
|
|
"dict2 = {}\n",
|
|
"for i in range(1,26):\n",
|
|
" dict1[f'q{str(i)}'] = 0\n",
|
|
" \n",
|
|
"list1 = []\n",
|
|
"filename = 'data/Survey_20230719.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",
|
|
"list2 = []\n",
|
|
"for result in list1:\n",
|
|
" data = json.loads(result[5].strip())\n",
|
|
" for k, v in data.items():\n",
|
|
" if v:\n",
|
|
" dict1[k] += 1\n",
|
|
"print(dict1) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "ad102064-de18-41aa-9829-b9b398df53d6",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2023-07-19T05:18:48.000423Z",
|
|
"iopub.status.busy": "2023-07-19T05:18:47.999556Z",
|
|
"iopub.status.idle": "2023-07-19T05:18:48.014467Z",
|
|
"shell.execute_reply": "2023-07-19T05:18:48.013436Z",
|
|
"shell.execute_reply.started": "2023-07-19T05:18:48.000379Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"['10422', 'zsyxz1', '', '张斌', '35', '{\"q25\":true,\"q1\":false,\"q2\":false,\"q3\":false,\"q4\":true,\"q5\":true,\"q6\":true,\"q7\":true,\"q8\":false,\"q9\":true,\"q10\":false,\"q11\":false,\"q12\":false,\"q13\":false,\"q14\":false,\"q15\":true,\"q16\":false,\"q17\":false,\"q18\":false,\"q19\":true,\"q20\":false,\"q21\":true,\"q22\":false,\"q23\":false,\"q24\":true}', '2023-06-01 20:00:00']\n",
|
|
"['10424', 'zsyxz1', '', '余兴见', '85', '{\"q25\":true,\"q1\":false,\"q2\":true,\"q3\":false,\"q4\":true,\"q5\":true,\"q6\":false,\"q7\":true,\"q8\":true,\"q9\":true,\"q10\":false,\"q11\":true,\"q12\":true,\"q13\":false,\"q14\":false,\"q15\":true,\"q16\":true,\"q17\":true,\"q18\":false,\"q19\":false,\"q20\":false,\"q21\":true,\"q22\":true,\"q23\":false,\"q24\":true}', '2023-06-01 20:00:00']\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"dict1 = {}\n",
|
|
"dict2 = {}\n",
|
|
"for i in range(1,26):\n",
|
|
" dict1[f'q{str(i)}'] = 0\n",
|
|
" \n",
|
|
"list1 = []\n",
|
|
"filename = 'data/Survey_20230719.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",
|
|
"list2 = []\n",
|
|
"for result in list1:\n",
|
|
" data = json.loads(result[5].strip())\n",
|
|
" for k, v in data.items():\n",
|
|
" if k == 'q25'and v:\n",
|
|
" print(result)\n",
|
|
"#print(dict1) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2787bc9f-6492-4b51-9b37-87ac098d93b9",
|
|
"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
|
|
}
|