2917 lines
86 KiB
Plaintext
2917 lines
86 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "19280f5c-8e34-4a64-8dfb-6353cbf597d2",
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"metadata": {
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"tags": [],
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"toc-hr-collapsed": true
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},
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"source": [
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"# 体质检测数据处理"
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]
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},
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{
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"cell_type": "markdown",
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"id": "112d80f4-607b-41f9-bb30-ac2eb8f52ee2",
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"metadata": {
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"jp-MarkdownHeadingCollapsed": true,
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"tags": []
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},
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"source": [
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"## 基础数据管理"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9a06725f-248b-44dd-b029-c18e7c0689ee",
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"metadata": {},
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"source": [
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"### 体测数据按编号汇总"
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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": "47aa588c-1880-44a8-add0-6fad777065d6",
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"metadata": {},
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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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"bh = set()\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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"list2 = []\n",
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"rq = '20240612'\n",
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"filename = f'data/places_result_{rq}.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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" bh.add(line[2])\n",
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" \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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" \n",
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" m_item = str(result[3]) \n",
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" re_ta.setdefault(user,{}) \n",
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" \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",
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"\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','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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"list1 = []\n",
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"for k, v in re_ta.items():\n",
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" list2 = []\n",
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" list2.append(str(k))\n",
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" for item in items:\n",
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" if item in v.keys():\n",
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" list2.append(v[item]['成绩']) \n",
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" elif item =='name':\n",
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" list2.append(v[item])\n",
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" else:\n",
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" list2.append('') \n",
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" list1.append(list2)\n",
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"filename = f'data/长炼医院体测情况表({rq}).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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"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": "b7dfd50f-a614-497d-8f0a-fa1e4c89168a",
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"metadata": {},
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"source": [
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"### 体测项目标准导入"
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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": "8cd73044-56a8-409b-a873-085feb63af17",
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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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"tcbz ={\n",
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" 'HeightWeigh':'身高体重',\n",
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" 'StepExperiment':'台阶指数',\n",
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" 'Lung':'肺活量',\n",
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" 'Proneness':'坐位体前屈',\n",
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" 'PowerfullGrip':'握力',\n",
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" 'OneMinutePushUp':'一分钟仰卧起坐',\n",
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" 'PushUp':'俯卧撑',\n",
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" 'VerticalJump':'纵跳',\n",
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" 'ReactionTime':'选择反应时',\n",
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" 'FootStand':'单脚站立'\n",
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"}\n",
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"wb = openpyxl.load_workbook('data/体质检测标准.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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"for k, v in tcbz.items():\n",
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" dict3[v] = k\n",
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"sheet = wb.active\n",
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"data1 =list(sheet.values)\n",
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"del data1[0]\n",
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"for item in data1:\n",
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" sex = item[0][6:]\n",
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" if sex =='男':\n",
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" age_sex = 'M'+item[0][:5]\n",
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" else:\n",
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" age_sex = 'F'+item[0][:5]\n",
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" dict1.setdefault(age_sex,{})\n",
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" if item[1] in dict3.keys():\n",
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" xm = dict3[item[1]]\n",
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" dict1[age_sex].setdefault(xm,[])\n",
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" dict1[age_sex][xm].append(item[3]/item[4])\n",
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"dict2 = {}\n",
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"#print(dict1)\n",
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"for k, v in dict1.items():\n",
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" i1 = int(k[1:3])\n",
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" i2 = int(k[-2:])\n",
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" m_sex = k[:1]\n",
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" for i in range(i1,i2+1):\n",
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" dict2[m_sex+str(i)] = k\n",
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"dict3 = {}\n",
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"dict3['person'] = dict2\n",
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"dict3['criteria'] = dict1\n",
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"filename = 'data/体质检测标准.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(dict3, 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": "c36641d8-c54b-43d2-ad9d-ff4cb72deba9",
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"metadata": {},
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"source": [
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"### 身高标准导入"
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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": "2ca52d7b-d77e-452f-98f6-95072a5a1934",
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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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"tcbz ={\n",
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" 'HeightWeigh':'身高体重',\n",
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" 'StepExperiment':'台阶指数',\n",
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" 'Lung':'肺活量',\n",
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" 'Proneness':'坐位体前屈',\n",
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" 'PowerfullGrip':'握力',\n",
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" 'OneMinutePushUp':'一分钟仰卧起坐',\n",
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" 'PushUp':'俯卧撑',\n",
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" 'VerticalJump':'纵跳',\n",
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" 'ReactionTime':'选择反应时',\n",
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" 'FootStand':'单脚站立'\n",
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"}\n",
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"wb = openpyxl.load_workbook('data/体质检测标准_BMI.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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"for k, v in tcbz.items():\n",
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" dict3[v] = k\n",
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"sheet = wb.active\n",
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"data1 =list(sheet.values)\n",
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"del data1[0]\n",
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"for item in data1:\n",
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" min_age = int(item[1]/12)\n",
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" max_age = int((item[2]+1)/12) - 1\n",
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" sex = item[0]\n",
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" height = int(item[3])\n",
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" if sex ==0:\n",
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" age_sex = 'M'+str(min_age)+'~'+str(max_age)\n",
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" else:\n",
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" age_sex = 'F'+str(min_age)+'~'+str(max_age)\n",
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" dict1.setdefault(age_sex,{})\n",
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" \n",
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" dict1[age_sex].setdefault(height,[])\n",
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" dict1[age_sex][height].append(item[5]/1000)\n",
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"dict2 = {}\n",
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"#print(dict1)\n",
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"for k, v in dict1.items():\n",
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" i1 = int(k[1:3])\n",
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" i2 = int(k[-2:])\n",
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" m_sex = k[:1]\n",
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" for i in range(i1,i2+1):\n",
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" dict2[m_sex+str(i)] = k\n",
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"dict3 = {}\n",
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"dict3['person'] = dict2\n",
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"dict3['criteria'] = dict1\n",
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"filename = 'data/体质检测标准_BMI.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(dict3, 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": "ad5a702c-1503-463f-9d02-b78b881aad1b",
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"metadata": {},
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"source": [
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"### 生成项目信息"
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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": "5071c245-3fdb-4c16-8f15-998af7c1d2fe",
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"metadata": {},
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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 = '../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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" del item[k]['divisor']\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/体质检测项目信息.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(item, 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": "59f5708d-c2d0-4470-b2f4-b9face431865",
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"metadata": {},
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"source": [
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"### 计算分数"
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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": "f32b266a-7e46-4703-ab61-7cbbc81b5ab1",
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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 = 'data/体质检测标准.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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"person = dict1['person']\n",
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"criteria = dict1['criteria']\n",
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"data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46}\n",
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"info = data['sex']+str(data['age'])\n",
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"bz = person[info]\n",
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"mx = criteria[bz][data['item']]\n",
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"result = data['result']\n",
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"score = -1\n",
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"print(mx)\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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"#if score == -1:\n",
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" # score = 5\n",
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"print(score)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "755f8b66-c71c-4138-bd12-dff24e85e36a",
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"metadata": {},
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"source": [
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"### 计算BMI分数"
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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": "b32fbbdd-eb0a-4f0d-8901-e39a727c3ff8",
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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 = 'data/体质检测标准_BMI.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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"person = dict1['person']\n",
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"criteria = dict1['criteria']\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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"info = data['sex']+str(data['age'])\n",
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"\n",
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"bz = person[info]\n",
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"print(bz)\n",
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"result = data['result']\n",
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"print(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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"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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"print(score)"
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]
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},
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{
|
|
"cell_type": "markdown",
|
|
"id": "7fe0ffe8-c3d1-4843-9765-87d4a12b7c39",
|
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"metadata": {},
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"source": [
|
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"## 体测报告生成"
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]
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},
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{
|
|
"cell_type": "markdown",
|
|
"id": "9fec0bfc-8a97-446f-95fe-6e9cf8e482d8",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 转换报告格式"
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|
]
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},
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|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "3e614f4a-a623-48e2-97f8-b31f62c9a983",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"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/天津石化人员2024.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_20241104.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",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append(line)\n",
|
|
"#f_item = ['lung','grip','flexion','jump','balance','reaction','step','situp']\n",
|
|
"#m_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
|
|
"for result in list1:\n",
|
|
" user = str(result[2])\n",
|
|
" rq = date.fromisoformat(result[6].replace('/','-'))\n",
|
|
" if user in dict1.keys():\n",
|
|
" l_xm = []\n",
|
|
" m_item = str(result[3]) \n",
|
|
" re_ta.setdefault(user,{}) \n",
|
|
" re_ta[user]['name'] = dict1[user]['name']\n",
|
|
" re_ta[user]['sex'] = dict1[user]['sex']\n",
|
|
" if dict1[user]['sex'] == '男':\n",
|
|
" l_xm = ['weight','height','lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
|
|
" else:\n",
|
|
" l_xm = ['weight','height','lung','grip','flexion','jump','balance','reaction','step','situp']\n",
|
|
" re_ta[user]['unit'] = dict1[user]['unit']\n",
|
|
" #birth = date.fromisoformat(dict1[user]['birth'].replace('/','-'))\n",
|
|
" birth = date.fromisoformat(dict1[user]['birth'])\n",
|
|
" #nian = int(birth[0].strip())\n",
|
|
" #yue = int(birth[1].strip())\n",
|
|
" #ri = int(birth[2].strip())\n",
|
|
" #print(k,nian,yue,ri)\n",
|
|
" item_name = item[m_item]['en'] \n",
|
|
" if item_name in l_xm: \n",
|
|
" days = (rq-birth).days \n",
|
|
" re_ta[user]['age'] = int(days/365)\n",
|
|
" re_ta[user]['month'] = int(days/365*12)\n",
|
|
" re_ta[user]['rq'] = result[6]\n",
|
|
"\n",
|
|
"\n",
|
|
" re_ta[user].setdefault(item_name,{}) \n",
|
|
" score = int(result[4])/item[m_item]['divisor'] \n",
|
|
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
|
"print(len(re_ta))\n",
|
|
"filename = 'data/result_天津石化2024.json'\n",
|
|
"\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
|
"print(len(re_ta))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6741916c-deb6-496f-bc8f-5248e107e0e9",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 生成完善得分"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "141b30dc-5975-4dcb-9bc3-9b20d26a0917",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"item = {}\n",
|
|
"unit = {}\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict3 = json.load(fl) \n",
|
|
"for k,v in dict3.items():\n",
|
|
" item[k] = v\n",
|
|
"item['1']['en'] = 'lung'\n",
|
|
"item['2']['en'] = 'grip'\n",
|
|
"item['3']['en'] = 'flexion'\n",
|
|
"item['4']['en'] = 'jump'\n",
|
|
"item['5']['en'] = 'pushup'\n",
|
|
"item['6']['en'] = 'balance'\n",
|
|
"item['7']['en'] = 'reaction'\n",
|
|
"item['8']['en'] = 'step'\n",
|
|
"item['9']['en'] = 'situp'\n",
|
|
"item['10']['en'] = 'height'\n",
|
|
"item['11']['en'] = 'weight'\n",
|
|
"\n",
|
|
"filename = 'data/体质检测标准 (1).json' \n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"def cal_score(data1):\n",
|
|
" #data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46} \n",
|
|
" person = dict1['person']\n",
|
|
" criteria = dict1['criteria']\n",
|
|
" if data1['age'] >59:\n",
|
|
" data1['age'] = 59\n",
|
|
" if data1['age'] <20:\n",
|
|
" data1['age'] = 20\n",
|
|
" info = data1['sex']+str(data1['age'])\n",
|
|
" bz = person[info]\n",
|
|
" mx = criteria[bz][data1['item']]\n",
|
|
" result = data1['result'] \n",
|
|
" if data1['item'] == 'reaction':\n",
|
|
" for bz1 in mx:\n",
|
|
" if result > bz1:\n",
|
|
" #print(bz1)\n",
|
|
" score = mx.index(bz1,0)\n",
|
|
" break\n",
|
|
" else:\n",
|
|
" score = 5\n",
|
|
" else:\n",
|
|
" for bz1 in mx:\n",
|
|
" if result < bz1:\n",
|
|
" #print(bz1)\n",
|
|
" score = mx.index(bz1,0)\n",
|
|
" break\n",
|
|
" else:\n",
|
|
" score = 5\n",
|
|
" return(score)\n",
|
|
"filename = 'data/体质检测标准_BMI.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict4 = json.load(fl) \n",
|
|
" \n",
|
|
"def cal_bmi(data1):\n",
|
|
" # data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n",
|
|
" person = dict4['person']\n",
|
|
" criteria = dict4['criteria']\n",
|
|
" if data1['age'] > 59:\n",
|
|
" data1['age'] = 59\n",
|
|
" if data1['age'] <20:\n",
|
|
" data1['age'] = 20\n",
|
|
" info = data1['sex']+str(data1['age'])\n",
|
|
" bz = person[info]\n",
|
|
" #print(bz)\n",
|
|
" result = data1['result']\n",
|
|
" #print(data1['code'],result)\n",
|
|
" height = int(float(result.split(',')[0]))\n",
|
|
" weight = float(result.split(',')[1])\n",
|
|
" if str(height) not in criteria[bz]:\n",
|
|
" score = 1\n",
|
|
" else: \n",
|
|
" mx = criteria[bz][str(height)]\n",
|
|
" if weight < mx[0]:\n",
|
|
" score = 1\n",
|
|
" elif weight < mx[1]:\n",
|
|
" score = 3\n",
|
|
" elif weight < mx[2]:\n",
|
|
" score = 5 \n",
|
|
" elif weight <= mx[3]:\n",
|
|
" score = 3 \n",
|
|
" elif weight > mx[3]:\n",
|
|
" score = 1\n",
|
|
" return score\n",
|
|
" \n",
|
|
" \n",
|
|
"\n",
|
|
"#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
|
|
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
|
|
"filename = 'data/result_天津石化2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict2 = json.load(fl) \n",
|
|
"for k, v in dict2.items():\n",
|
|
" #print(k)\n",
|
|
" if v['sex'] == '男':\n",
|
|
" sex = 'M'\n",
|
|
" else:\n",
|
|
" sex = 'F' \n",
|
|
" if 'height' in v.keys() and 'weight' in v.keys():\n",
|
|
" bmi_data = v['height']['成绩'].split()[0]+','+ v['weight']['成绩'].split()[0]\n",
|
|
" data1 = {'code':k,'sex':sex,'age':v['age'],'item':'HeightWeight','result':bmi_data}\n",
|
|
" dict2[k]['bmi'] = {}\n",
|
|
" dict2[k]['bmi']['成绩'] = bmi_data\n",
|
|
" dict2[k]['bmi']['score'] = cal_bmi(data1)\n",
|
|
" for item_en in list_item:\n",
|
|
" if item_en in v.keys(): \n",
|
|
" data1 = {'code':k,'sex':sex,'age':v['age'],'item':item_en,'result':float(v[item_en]['成绩'].split()[0])}\n",
|
|
" dict2[k][item_en]['score'] = cal_score(data1)\n",
|
|
" #print(k,v[item_en]['成绩'],cal_score(data1))\n",
|
|
"\n",
|
|
"filename = f'data/result_天津石化2024.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict2,fl , ensure_ascii=False) \n",
|
|
"print('ok!') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ceef0742-f62a-4a7d-b0d5-be7ae7abb741",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 生成报告"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "b123ee6b-85d2-4660-b226-321832a6b796",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-05T01:54:15.911722Z",
|
|
"iopub.status.busy": "2024-12-05T01:54:15.910983Z",
|
|
"iopub.status.idle": "2024-12-05T02:00:21.680493Z",
|
|
"shell.execute_reply": "2024-12-05T02:00:21.679283Z",
|
|
"shell.execute_reply.started": "2024-12-05T01:54:15.911657Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"738\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import requests\n",
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"\n",
|
|
"headers = {\n",
|
|
" \"Content-Type\": \"application/json; charset=UTF-8\"\n",
|
|
" }\n",
|
|
"filename = 'data/result_北海炼化2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"list1 = []\n",
|
|
"file_path ='./北海炼化2024/'\n",
|
|
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
|
|
"i=0\n",
|
|
"list2 = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" list1 = []\n",
|
|
" mydata = {}\n",
|
|
" \n",
|
|
" id = str(k).rjust(4,\"0\")\n",
|
|
" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
|
|
" mydata['title'] = '中国石化北海炼化有限责任公司'\n",
|
|
" mydata['subtitle'] = v['unit']\n",
|
|
" mydata['id'] = id\n",
|
|
" mydata['name'] = v['name']\n",
|
|
" if v['sex'] == '男':\n",
|
|
" mydata['gender'] = 'male'\n",
|
|
" else:\n",
|
|
" mydata['gender'] = 'female'\n",
|
|
" \n",
|
|
" mydata['month'] = v['month']\n",
|
|
" mydata['fits'] = {}\n",
|
|
" survey_list = ['tcm','psy','spine']\n",
|
|
" for item in survey_list:\n",
|
|
" if item in v.keys():\n",
|
|
" mydata.setdefault('surveys',{})\n",
|
|
" mydata['surveys'][item] = v[item]\n",
|
|
" \n",
|
|
" \n",
|
|
" #mydata['fits'] = {}\n",
|
|
" for item in list_item:\n",
|
|
" if item in v.keys():\n",
|
|
" mydata.setdefault('fits',{})\n",
|
|
" if item in ['lung','pushup','step','situp']:\n",
|
|
" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
|
|
" else:\n",
|
|
" mark = v[item]['成绩'].split()[0]\n",
|
|
" mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
|
|
" #if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
|
|
" if len(mydata['fits']) >2 : \n",
|
|
" list1.append(mydata)\n",
|
|
" list2.append([k,v['name']])\n",
|
|
" i+=1\n",
|
|
" x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
|
|
" #print(id,v['name'],x.text)\n",
|
|
" #print(mydata)\n",
|
|
" #x.close()\n",
|
|
"print(i)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "4c1b3696-ab24-44bd-894a-e271ecfe4e38",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import requests\n",
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"\n",
|
|
"headers = {\n",
|
|
" \"Content-Type\": \"application/json; charset=UTF-8\"\n",
|
|
" }\n",
|
|
"filename = 'data/result_东营工程设计院2024_all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"list1 = []\n",
|
|
"file_path ='./中石化石油工程设计有限公司/'\n",
|
|
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
|
|
"i=0\n",
|
|
"list2 = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" list1 = []\n",
|
|
" mydata = {}\n",
|
|
" \n",
|
|
" id = str(k).rjust(4,\"0\")\n",
|
|
" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
|
|
" mydata['title'] = '中石化石油工程设计有限公司'\n",
|
|
" mydata['subtitle'] = v['unit']\n",
|
|
" mydata['id'] = id\n",
|
|
" mydata['name'] = v['name']\n",
|
|
" if v['sex'] == '男':\n",
|
|
" mydata['gender'] = 'male'\n",
|
|
" else:\n",
|
|
" mydata['gender'] = 'female'\n",
|
|
" \n",
|
|
" mydata['month'] = v['month']\n",
|
|
" mydata['fits'] = {}\n",
|
|
" survey_list = ['tcm','psy','spine']\n",
|
|
" for item in survey_list:\n",
|
|
" if item in v.keys():\n",
|
|
" mydata.setdefault('surveys',{})\n",
|
|
" mydata['surveys'][item] = v[item]\n",
|
|
" \n",
|
|
" \n",
|
|
" #mydata['fits'] = {}\n",
|
|
" for item in list_item:\n",
|
|
" if item in v.keys():\n",
|
|
" mydata.setdefault('fits',{})\n",
|
|
" if item in ['lung','pushup','step','situp']:\n",
|
|
" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
|
|
" else:\n",
|
|
" mark = v[item]['成绩'].split()[0]\n",
|
|
" mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
|
|
" #if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
|
|
" \n",
|
|
" list1.append(mydata)\n",
|
|
" list2.append([k,v['name']])\n",
|
|
" i+=1\n",
|
|
" x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
|
|
" #print(id,v['name'],x.text)\n",
|
|
" #print(mydata)\n",
|
|
" #x.close()\n",
|
|
"print(i)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4642faf7-52bf-40e9-9af3-7555d4eef10b",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 体测报告按部门分类"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d913a531-51b3-4795-adc3-f4fc858d7401",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/pdf-typescript/中石化石油工程设计有限公司1'\n",
|
|
"new_path = 'file/中石化石油工程设计有限公司1'\n",
|
|
"old = []\n",
|
|
"dict2 = {}\n",
|
|
"\n",
|
|
"filename = 'data/东营工程设计院2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"for fn in fls:\n",
|
|
" fi_name =Path(fn).stem.split('-')[0]\n",
|
|
" code = int(fi_name)\n",
|
|
" unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
|
|
" unit_path.mkdir(parents = True, exist_ok = True)\n",
|
|
" n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
|
|
" if not os.path.exists(n_name):\n",
|
|
" shutil.copyfile(fn,n_name)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1e6ece92-7845-49df-a84c-88a2befee570",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 生成体测报告打印明细表"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "02319955-7fb6-4791-ae45-55b03bdadd54",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/pdf-typescript/北海炼化2024'\n",
|
|
"\n",
|
|
"filename = 'data/中安联合.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"list1 = []\n",
|
|
"title = ['测试编号','姓名','性别','部门']\n",
|
|
"for fn in fls:\n",
|
|
" list2 = []\n",
|
|
" fi_name =Path(fn).stem.split('-')[0] \n",
|
|
" code = int(fi_name)\n",
|
|
" sex = dict1[str(code)]['sex']\n",
|
|
" unit = dict1[str(code)]['unit']\n",
|
|
" list2 = [fi_name,Path(fn).stem.split('-')[1],sex,unit]\n",
|
|
" \n",
|
|
" list1.append(list2)\n",
|
|
"\n",
|
|
"filename = 'data/中安联合体测报告明细表.xlsx'\n",
|
|
"wb = openpyxl.Workbook()\n",
|
|
"sheet = wb.active\n",
|
|
"sheet.append(title)\n",
|
|
"for row in list1:\n",
|
|
" sheet.append(row)\n",
|
|
" \n",
|
|
"wb.save(filename) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "34ef7e0d-35ea-4739-a1cb-540c5039afb7",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 检查报告错误人员"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"id": "c464fa11-8a0d-44e9-8af0-8c1f50263ceb",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-05T02:12:16.971166Z",
|
|
"iopub.status.busy": "2024-12-05T02:12:16.970399Z",
|
|
"iopub.status.idle": "2024-12-05T02:12:16.991930Z",
|
|
"shell.execute_reply": "2024-12-05T02:12:16.991373Z",
|
|
"shell.execute_reply.started": "2024-12-05T02:12:16.971124Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"739\n",
|
|
"518\n",
|
|
"275\n",
|
|
"809\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import os,sys,shutil\n",
|
|
"import json\n",
|
|
"import glob\n",
|
|
"from pathlib import Path\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"fi_path = '/home/songyi/pdf-typescript/北海炼化2024'\n",
|
|
"\n",
|
|
"filename = 'data/result_北海炼化2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"print(len(dict1))\n",
|
|
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
|
"list1 = []\n",
|
|
"for fn in fls: \n",
|
|
" fi_name =Path(fn).stem.split('-')[0] \n",
|
|
" code = int(fi_name)\n",
|
|
" list1.append(str(code))\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if k not in list1:\n",
|
|
" print(k)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "732161bb-98f2-4861-ab66-7a374678bcd8",
|
|
"metadata": {
|
|
"jp-MarkdownHeadingCollapsed": true,
|
|
"tags": [],
|
|
"toc-hr-collapsed": true
|
|
},
|
|
"source": [
|
|
"# 体质检测数据管理"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "bb2db5e8-5dc6-4366-a39c-a3600ee5007c",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 数据导入Mycrm"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "bc98d772-5841-41a3-ad8f-f7d1ff3b5fde",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入系统人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2cd93f45-6613-4a3f-97e4-5236068e1860",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import time\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"list1 = []\n",
|
|
"filename = 'data/person_134.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",
|
|
"dict1 = {}\n",
|
|
"for result in list1:\n",
|
|
" code = str(result[4])\n",
|
|
" if int(result[1]) == 0:\n",
|
|
" sex = '男'\n",
|
|
" else:\n",
|
|
" sex = '女'\n",
|
|
" \n",
|
|
" m_item = str(result[3]) \n",
|
|
" dict1.setdefault(code,{}) \n",
|
|
" dict1[code]['name'] = result[0]\n",
|
|
" dict1[code]['sex'] = sex\n",
|
|
" dict1[code]['birth'] = result[2]\n",
|
|
"filename = 'data/天津石化人员清单.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
|
"print(len(dict1)) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2eb50f19-c15f-4a36-87b7-cd02551d248d",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入测试项目item"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0eb37435-9c15-40ef-bd4c-2dffc026f59e",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"data_list = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" data_list.append((int(k),v['name'])) \n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
"sql = 'insert into shijiazhuang_item (id,name) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "2ba97298-1e7e-4192-8d69-ea59f98e071a",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入一级部门"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9f7ed380-95f3-47d4-9eb5-74937af7811f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
"filename = 'data/result_石家庄.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"unit = set()\n",
|
|
"for k, v in dict1.items():\n",
|
|
" #if 'sub_unit' not in v.keys():\n",
|
|
" # print(k,v['name'])\n",
|
|
" unit.add(v['unit'])\n",
|
|
"print(unit) \n",
|
|
"i = 1\n",
|
|
"dict2 = {}\n",
|
|
"for item in unit:\n",
|
|
" dict2[item] = i\n",
|
|
" i+=1\n",
|
|
"data_list = []\n",
|
|
"for k, v in dict2.items():\n",
|
|
" data_list.append((v,k)) \n",
|
|
" \n",
|
|
"sql = 'insert into shijiazhuang_unit (id,name) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "b8a1fa7f-08ff-49bb-8052-9f86b1f2ac18",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入二级部门"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a13e81f2-467f-42c7-bb46-b547ef7bdd6c",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
"filename = 'data/天津石化人员名单.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"unit = set()\n",
|
|
"for k, v in dict1.items():\n",
|
|
" #if 'sub_unit' not in v.keys():\n",
|
|
" # print(k,v['name'])\n",
|
|
" unit.add(v['unit'])\n",
|
|
"print(unit) \n",
|
|
"i = 1\n",
|
|
"dict2 = {}\n",
|
|
"for item in unit:\n",
|
|
" dict2[item] = i\n",
|
|
" i+=1\n",
|
|
"data_list = []\n",
|
|
"dict3 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" dict3.setdefault(v['unit'],set())\n",
|
|
" dict3[v['unit']].add(v['sub_unit'])\n",
|
|
"i = 1 \n",
|
|
"for k, v in dict3.items():\n",
|
|
" unit_id = dict2[k]\n",
|
|
" for item in v:\n",
|
|
" data_list.append((i,item,unit_id))\n",
|
|
" i+=1\n",
|
|
"sql = 'insert into tianjin_sub_unit (id,name,unit_id) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "12917000-59e0-4f8a-beee-929c6d7b60a0",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 生成部门JSON文件"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5446269c-d324-4a16-b10e-f24d87178d77",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"dict1 = {}\n",
|
|
"filename = 'data/shijiazhuang_unit_20230517.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl)\n",
|
|
" list1 = []\n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append({'id':int(line[0]),'name':line[1]})\n",
|
|
"dict1['unit'] = list1\n",
|
|
"\n",
|
|
"filename = 'data/sub_unit_134.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl)\n",
|
|
" list1 = []\n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append({'id':int(line[0]),'name':line[1],'unit_id':int(line[2])})\n",
|
|
"dict1['sub_unit'] = list1\n",
|
|
"print(dict1)\n",
|
|
"\n",
|
|
"filename = 'data/天津石化部门.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
|
"print(len(dict1)) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5e57329d-a0ef-47b2-9866-fe2a911ff01d",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import csv\n",
|
|
"\n",
|
|
"dict1 = {}\n",
|
|
"filename = 'data/shijiazhuang_unit_20230517.csv'\n",
|
|
"with open(filename,'r',newline='') as csv_file:\n",
|
|
" fl = csv.reader(csv_file,delimiter=',')\n",
|
|
" header = next(fl)\n",
|
|
" list1 = []\n",
|
|
" for line in fl:\n",
|
|
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
|
" list1.append({'id':int(line[0]),'name':line[1]})\n",
|
|
" dict1[int(line[0])] = line[1]\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/石家庄石化部门.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
|
"print(len(dict1)) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "53bf98fe-0ae9-402f-b8d8-495e8f31df3d",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入人员信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6af82fd2-b1d6-44b7-8b13-58883b58f8b0",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
"filename = 'data/天津石化人员清单.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" person = json.load(fl)\n",
|
|
" \n",
|
|
"filename = 'data/石家庄石化部门.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"i = 1\n",
|
|
"dict2 = {}\n",
|
|
"for item in unit:\n",
|
|
" dict2[item] = i\n",
|
|
" i+=1\n",
|
|
"data_list = []\n",
|
|
"dict3 = {}\n",
|
|
"dict4 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" dict3.setdefault(v['unit'],set())\n",
|
|
" dict3[v['unit']].add(v['sub_unit']) \n",
|
|
"i = 1 \n",
|
|
"for k, v in dict3.items():\n",
|
|
" unit_id = dict2[k]\n",
|
|
" for item in v:\n",
|
|
" data_list.append((i,item,unit_id))\n",
|
|
" i+=1\n",
|
|
"for item in data_list:\n",
|
|
" sub_id = item[0]\n",
|
|
" dict4[sub_id] = {'name':item[1],'unit':item[2]}\n",
|
|
"dict5 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" id_unit = dict2[v['unit']]\n",
|
|
" sub_name = v['sub_unit']\n",
|
|
" id_sub = 0\n",
|
|
" for k1, v1 in dict4.items():\n",
|
|
" if v1['name'] == sub_name and v1['unit'] == id_unit:\n",
|
|
" id_sub = int(k1)\n",
|
|
" if id_sub >0:\n",
|
|
" dict5[k] = {'unit':id_unit,'sub_unit':id_sub}\n",
|
|
" else:\n",
|
|
" print(k,'not fund')\n",
|
|
"data_list = []\n",
|
|
"for k, v in dict5.items():\n",
|
|
" id = int(k)\n",
|
|
" name = person[k]['name']\n",
|
|
" sex = person[k]['sex']\n",
|
|
" birth = person[k]['birth']\n",
|
|
" phone = ''\n",
|
|
" note = ''\n",
|
|
" unit = v['sub_unit']\n",
|
|
" data_list.append((id,name,sex,birth,unit))\n",
|
|
"sql = 'insert into tianjin_person (id,name,sex,birth,unit_id) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!') \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c2007c46-38c8-4a20-9917-b0b8743fe2a9",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
" \n",
|
|
"filename = 'data/石家庄石化部门.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"dict3 = {}\n",
|
|
"for k,v in dict1.items():\n",
|
|
" dict3[v] = int(k)\n",
|
|
"filename = 'data/result_石家庄.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict2 = json.load(fl)\n",
|
|
"data_list = []\n",
|
|
"for k, v in dict2.items():\n",
|
|
" id = int(k)\n",
|
|
" name = dict2[k]['name']\n",
|
|
" sex = dict2[k]['sex']\n",
|
|
" birth = dict2[k]['birth'] \n",
|
|
" unit = dict3[dict2[k]['unit']]\n",
|
|
" data_list.append((id,name,sex,birth,unit))\n",
|
|
"sql = 'insert into shijiazhuang_person (id,name,sex,birth,unit_id) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "fd95a45a-c6df-47c3-9941-2d0579b2c5d9",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 导入测试成绩及得分"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "c989de3f-a8ab-47dc-9662-544e4b6a0e2f",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"#### 二级部门导入"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "360e61e9-7895-484b-a9d6-333bdefa1a86",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" dict2[v['name']] = int(k)\n",
|
|
"\n",
|
|
"filename = 'data/天津石化部门.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"unit = {}\n",
|
|
"for item in dict1['unit']:\n",
|
|
" unit[item['name']] = item['id']\n",
|
|
"\n",
|
|
"sub_unit = {}\n",
|
|
"for item in dict1['sub_unit']:\n",
|
|
" sub_unit.setdefault(item['unit_id'],[])\n",
|
|
" sub_unit[item['unit_id']].append({'id':item['id'],'name':item['name']})\n",
|
|
" \n",
|
|
"filename = 'data/天津石化人员名单.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"person = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" person[k] = {'unit':v['unit'],'sub_unit':v['sub_unit']}\n",
|
|
"\n",
|
|
" \n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
"data_list = []\n",
|
|
"filename = 'data/result_天津.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k, v in dict1.items():\n",
|
|
" for item in v.keys():\n",
|
|
" if item in dict2.keys():\n",
|
|
" item_id = dict2[item]\n",
|
|
" if v[item]['得分'] == '\\\\N':\n",
|
|
" score = None\n",
|
|
" else:\n",
|
|
" score = int(v[item]['得分'])\n",
|
|
" unit_name = person[k]['unit'] \n",
|
|
" sub_unit_name = person[k]['sub_unit']\n",
|
|
" unit_id = unit[unit_name]\n",
|
|
" for items in sub_unit[unit_id]:\n",
|
|
" if items['name'] ==sub_unit_name:\n",
|
|
" sub_id = items['id'] \n",
|
|
" data_list.append((v[item]['成绩'],score,int(k),item_id,unit_id,sub_id))\n",
|
|
" \n",
|
|
"sql = 'insert into tianjin_records (performance,score,avatar_id_id,item_id_id,unit_id_id,sub_unit_id_id) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!') \n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4aeabbbc-5b51-4dd0-b428-83e2012e63c4",
|
|
"metadata": {},
|
|
"source": [
|
|
"#### 一级部门导入"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "cb747368-d3ac-4b29-ae4f-ce207d5fcd43",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" dict2[v['name']] = int(k)\n",
|
|
"\n",
|
|
"filename = 'data/石家庄石化部门.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"dict3 = {}\n",
|
|
"for k,v in dict1.items():\n",
|
|
" dict3[v] = int(k)\n",
|
|
" \n",
|
|
"\n",
|
|
"conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n",
|
|
"cursor = conn.cursor()\n",
|
|
"data_list = []\n",
|
|
"filename = 'data/result_石家庄.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k, v in dict1.items():\n",
|
|
" for item in v.keys():\n",
|
|
" if item in dict2.keys():\n",
|
|
" item_id = dict2[item] \n",
|
|
" if v[item]['得分'] == '':\n",
|
|
" score = None\n",
|
|
" else:\n",
|
|
" score = int(v[item]['得分'])\n",
|
|
" unit_name = v['unit']\n",
|
|
" unit_id = dict3[unit_name]\n",
|
|
" data_list.append((v[item]['成绩'],score,int(k),item_id,unit_id))\n",
|
|
"sql = 'insert into shijiazhuang_records (performance,score,avatar_id_id,item_id_id,unit_id_id) values %s'\n",
|
|
"ex.execute_values(cursor, sql, data_list, page_size=10000)\n",
|
|
"#conn.commit()\n",
|
|
"cursor.close()\n",
|
|
"conn.close()\n",
|
|
"print('ok!')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "51dc35a5-dc07-40a4-9ea7-375ca7f983c3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import psycopg2\n",
|
|
"from psycopg2 import extras as ex\n",
|
|
"\n",
|
|
"filename = '../item.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" dict2[v['name']] = int(k)\n",
|
|
"\n",
|
|
"filename = 'data/天津石化部门.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"unit = {}\n",
|
|
"for item in dict1['unit']:\n",
|
|
" unit[item['name']] = item['id']\n",
|
|
"print(unit)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "5780368e-59c7-4bc1-a130-21b2f7da23de",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 体质测试综合报告数据分析"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "0ddf1a23-5963-43ba-9166-c88be749d75d",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 清理报告数据"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 35,
|
|
"id": "46aa847d-e1fe-45bd-85b6-e2d792ec8842",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-11-07T11:47:37.575532Z",
|
|
"iopub.status.busy": "2024-11-07T11:47:37.574781Z",
|
|
"iopub.status.idle": "2024-11-07T11:47:37.780926Z",
|
|
"shell.execute_reply": "2024-11-07T11:47:37.780418Z",
|
|
"shell.execute_reply.started": "2024-11-07T11:47:37.575459Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"4059\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/result_天津石化2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
" \n",
|
|
"#items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
|
"items = {}\n",
|
|
"items['lung'] = '肺活量'\n",
|
|
"items['grip'] ='握力'\n",
|
|
"items['flexion'] ='坐位体前屈'\n",
|
|
"items['jump'] ='纵跳'\n",
|
|
"items['pushup'] ='俯卧撑'\n",
|
|
"items['balance'] ='单脚站立'\n",
|
|
"items['reaction'] ='选择反应时'\n",
|
|
"items['step'] ='台阶指数'\n",
|
|
"items['situp'] ='一分钟仰卧起坐'\n",
|
|
"items['bmi'] ='BMI'\n",
|
|
"\n",
|
|
"\n",
|
|
"list1 = []\n",
|
|
"#fiie_path ='./138/'\n",
|
|
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
|
|
"i=1\n",
|
|
"list2 = []\n",
|
|
"dict2 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" list1 = []\n",
|
|
" mydata = {}\n",
|
|
" \n",
|
|
" id = str(k).rjust(8,\"0\")\n",
|
|
" mydata['unit'] = v['unit']\n",
|
|
" mydata['name'] = v['name']\n",
|
|
" mydata['sex'] = v['sex']\n",
|
|
" mydata['month'] = v['month']\n",
|
|
" age = int(v['month']/12)\n",
|
|
" if age <20:\n",
|
|
" mydata['age'] = 20\n",
|
|
" else:\n",
|
|
" mydata['age'] = int(v['month']/12)\n",
|
|
" \n",
|
|
" mydata['fits'] = {}\n",
|
|
" score = 0\n",
|
|
" for item in list_item:\n",
|
|
" if item in v.keys():\n",
|
|
" if item in ['lung','pushup','step','situp']:\n",
|
|
" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
|
|
" else:\n",
|
|
" mark = v[item]['成绩'].split()[0]\n",
|
|
" mydata['fits'][items[item]] = {'mark':mark,'score':v[item]['score']}\n",
|
|
" score = score + v[item]['score']\n",
|
|
" mydata['score'] = round(score/len(mydata['fits']),2)\n",
|
|
" if len(mydata['fits']) >2:\n",
|
|
" dict2[str(k)] = mydata\n",
|
|
"filename = f'data/data_天津石化2024.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict2,fl , ensure_ascii=False) \n",
|
|
"print(len(dict2)) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ed5f157a-3114-4221-907d-53ce62409d83",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算平均成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "63edd636-f034-4aa6-8575-63d5cdb84adb",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:02:47.958778Z",
|
|
"iopub.status.busy": "2024-12-04T15:02:47.958038Z",
|
|
"iopub.status.idle": "2024-12-04T15:02:47.975696Z",
|
|
"shell.execute_reply": "2024-12-04T15:02:47.974632Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:02:47.958708Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"平均成绩：2.9551分，男性：598人\n",
|
|
"平均成绩：3.1705分，女性：140人\n",
|
|
"平均成绩：2.996分，总体：738人\n"
|
|
]
|
|
}
|
|
],
|
|
"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/data_北海炼化2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"i = 1\n",
|
|
"m = 0\n",
|
|
"f = 0\n",
|
|
"score = 0\n",
|
|
"t_score = 0\n",
|
|
"for k,v in dict1.items():\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" score = score+v['score']\n",
|
|
"print(f'平均成绩：{round(score/m,4)}分，男性：{m}人')\n",
|
|
"t_score = t_score + score\n",
|
|
"score = 0\n",
|
|
"for k,v in dict1.items():\n",
|
|
" if v['sex'] == '女':\n",
|
|
" f = f +1\n",
|
|
" score = score+v['score']\n",
|
|
"print(f'平均成绩：{round(score/f,4)}分，女性：{f}人')\n",
|
|
"t_score = t_score + score\n",
|
|
"print(f'平均成绩：{round(t_score/(f+m),4)}分，总体：{(f+m)}人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3277b104-9b53-41c4-9b9a-f9acb71dbce1",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算测试等级"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "1b4a3f02-9b2e-41fc-ac6c-8163907a07f1",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:03:47.530784Z",
|
|
"iopub.status.busy": "2024-12-04T15:03:47.530057Z",
|
|
"iopub.status.idle": "2024-12-04T15:03:47.570098Z",
|
|
"shell.execute_reply": "2024-12-04T15:03:47.569570Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:03:47.530717Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"0~255分人数：130人,男性：116人,女性:14人\n",
|
|
"256~332分人数：368人,男性：306人,女性:62人\n",
|
|
"333~367分人数：170人,男性：125人,女性:45人\n",
|
|
"368~500分人数：70人,男性：51人,女性:19人\n",
|
|
"738\n",
|
|
"ok\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
|
"\n",
|
|
"#filename = 'data/data_长炼医院.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"\n",
|
|
"for k1, v1 in dict2.items():\n",
|
|
" di = v1[0]\n",
|
|
" gao = v1[1]\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if int(v['score']*100) in range(di,gao+1):\n",
|
|
" dict1[k]['level'] = k1\n",
|
|
" i+=1\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" else:\n",
|
|
" f = f+1\n",
|
|
" print(f'{di}~{gao}分人数：{i}人,男性：{m}人,女性:{f}人')\n",
|
|
"print(len(dict1))\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "39a1239d-13d8-4583-a163-e6db98c3933b",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各年龄段测试等级(女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "2d661ca6-6129-4da1-ac25-51d0156babb2",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:04:19.067670Z",
|
|
"iopub.status.busy": "2024-12-04T15:04:19.066925Z",
|
|
"iopub.status.idle": "2024-12-04T15:04:19.087808Z",
|
|
"shell.execute_reply": "2024-12-04T15:04:19.087242Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:04:19.067602Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"20-24 {'不合格': 2, '良好': 6, '优秀': 0, '合格': 8}\n",
|
|
"25-29 {'良好': 11, '不合格': 2, '合格': 13, '优秀': 2}\n",
|
|
"30-34 {'合格': 8, '良好': 3, '优秀': 4, '不合格': 1}\n",
|
|
"35-39 {'优秀': 2, '良好': 7, '合格': 10, '不合格': 6}\n",
|
|
"40-44 {'优秀': 1, '良好': 4, '合格': 1, '不合格': 0}\n",
|
|
"45-49 {'合格': 20, '优秀': 5, '良好': 8, '不合格': 3}\n",
|
|
"50-54 {'合格': 2, '良好': 6, '优秀': 5, '不合格': 0}\n",
|
|
"55-80 {'优秀': 0, '合格': 0, '良好': 0, '不合格': 0}\n"
|
|
]
|
|
}
|
|
],
|
|
"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": "b7d10bef-405f-49a1-b423-2b972b4d1a44",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各年龄段测试等级(男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"id": "fc97df37-34ff-4a02-9d26-b5d81b706e46",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:07:08.531067Z",
|
|
"iopub.status.busy": "2024-12-04T15:07:08.530357Z",
|
|
"iopub.status.idle": "2024-12-04T15:07:08.545126Z",
|
|
"shell.execute_reply": "2024-12-04T15:07:08.544536Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:07:08.531002Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"20-24 {'不合格': 26, '良好': 9, '优秀': 2, '合格': 35}\n",
|
|
"25-29 {'良好': 20, '不合格': 25, '合格': 48, '优秀': 3}\n",
|
|
"30-34 {'合格': 24, '良好': 5, '优秀': 2, '不合格': 5}\n",
|
|
"35-39 {'优秀': 11, '良好': 23, '合格': 29, '不合格': 10}\n",
|
|
"40-44 {'优秀': 6, '良好': 3, '合格': 17, '不合格': 1}\n",
|
|
"45-49 {'合格': 37, '优秀': 6, '良好': 16, '不合格': 4}\n",
|
|
"50-54 {'合格': 73, '良好': 31, '优秀': 12, '不合格': 28}\n",
|
|
"55-80 {'优秀': 9, '合格': 43, '良好': 18, '不合格': 17}\n"
|
|
]
|
|
}
|
|
],
|
|
"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": "466355fe-5939-463c-a31e-a3a1beb4e78b",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 根据年龄汇总人员信息及成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "dafb86f8-5ee0-4c87-a98f-c7ff0f631fe5",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:07:14.121761Z",
|
|
"iopub.status.busy": "2024-12-04T15:07:14.119927Z",
|
|
"iopub.status.idle": "2024-12-04T15:07:14.142357Z",
|
|
"shell.execute_reply": "2024-12-04T15:07:14.141727Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:07:14.121677Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"16~24岁平均成绩：2.73分，人数：88人,男性：72人\n",
|
|
"25~29岁平均成绩：2.92分，人数：124人,男性：96人\n",
|
|
"30~34岁平均成绩：3.02分，人数：52人,男性：36人\n",
|
|
"35~39岁平均成绩：3.1分，人数：98人,男性：73人\n",
|
|
"40~44岁平均成绩：3.21分，人数：33人,男性：27人\n",
|
|
"45~49岁平均成绩：3.09分，人数：99人,男性：63人\n",
|
|
"50~54岁平均成绩：3.04分，人数：157人,男性：144人\n",
|
|
"55~69岁平均成绩：2.97分，人数：87人,男性：87人\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"nld = [[16,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1):\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" if i ==0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：0人,男性：{m}人')\n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人,男性：{m}人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "dafdffca-6543-4304-af61-4f7cd418ba24",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 根据年龄汇总人员信息及成绩（男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "347703a1-501b-4800-bd29-16e94f4a6793",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:10:04.572147Z",
|
|
"iopub.status.busy": "2024-12-04T15:10:04.571454Z",
|
|
"iopub.status.idle": "2024-12-04T15:10:04.596383Z",
|
|
"shell.execute_reply": "2024-12-04T15:10:04.595277Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:10:04.572082Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"20~24岁平均成绩：2.68分，人数：72人\n",
|
|
"25~29岁平均成绩：2.86分，人数：96人\n",
|
|
"30~34岁平均成绩：2.94分，人数：36人\n",
|
|
"35~39岁平均成绩：3.12分，人数：73人\n",
|
|
"40~44岁平均成绩：3.15分，人数：27人\n",
|
|
"45~49岁平均成绩：3.06分，人数：63人\n",
|
|
"50~54岁平均成绩：2.98分，人数：144人\n",
|
|
"55~80岁平均成绩：2.97分，人数：87人\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1) and v['sex'] == '男':\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if i ==0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：{i}人') \n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "9b63891e-824a-4772-83f9-0706381ffd14",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 根据年龄汇总人员信息及成绩（女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"id": "5900d1c7-2f8c-4dfa-a60e-a577fb90f22d",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:09:34.523177Z",
|
|
"iopub.status.busy": "2024-12-04T15:09:34.522550Z",
|
|
"iopub.status.idle": "2024-12-04T15:09:34.543633Z",
|
|
"shell.execute_reply": "2024-12-04T15:09:34.542960Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:09:34.523123Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"20~24岁平均成绩：2.94分，人数：16人\n",
|
|
"25~29岁平均成绩：3.13分，人数：28人\n",
|
|
"30~34岁平均成绩：3.19分，人数：16人\n",
|
|
"35~39岁平均成绩：3.07分，人数：25人\n",
|
|
"40~44岁平均成绩：3.49分，人数：6人\n",
|
|
"45~49岁平均成绩：3.15分，人数：36人\n",
|
|
"50~54岁平均成绩：3.64分，人数：13人\n",
|
|
"55~80岁平均成绩：0分，人数：0人\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1) and v['sex'] == '女':\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if i ==0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：{i}人') \n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ca546652-d275-46d3-9b9a-9cb1c3a09a78",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算各项目成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"id": "ad69c45d-3f62-42df-894d-47424e759029",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:10:44.614467Z",
|
|
"iopub.status.busy": "2024-12-04T15:10:44.613711Z",
|
|
"iopub.status.idle": "2024-12-04T15:10:44.636541Z",
|
|
"shell.execute_reply": "2024-12-04T15:10:44.635981Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:10:44.614399Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"BMI 3.6 738\n",
|
|
"肺活量 3.38 728\n",
|
|
"握力 2.55 737\n",
|
|
"坐位体前屈 2.73 699\n",
|
|
"纵跳 2.53 692\n",
|
|
"俯卧撑 3.29 523\n",
|
|
"一分钟仰卧起坐 3.82 109\n",
|
|
"单脚站立 2.73 726\n",
|
|
"选择反应时 3.32 737\n",
|
|
"台阶指数 2.79 540\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
|
"for item in items:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items(): \n",
|
|
" if item in v['fits'].keys():\n",
|
|
" n = n + 1\n",
|
|
" score =score + int(v['fits'][item]['score'])\n",
|
|
" print(item,round(score/n,2),n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "f005328b-1927-4f62-b530-e7750299c423",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 按照部门计算平均成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "dcf152e7-bbcc-47d1-9c5f-83854db35412",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:12:44.516371Z",
|
|
"iopub.status.busy": "2024-12-04T15:12:44.515637Z",
|
|
"iopub.status.idle": "2024-12-04T15:12:44.537110Z",
|
|
"shell.execute_reply": "2024-12-04T15:12:44.536346Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:12:44.516304Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"炼油二部 2.96 136\n",
|
|
"公用工程部 2.99 53\n",
|
|
"储运部 2.9 101\n",
|
|
"炼油一部 3.0 122\n",
|
|
"炼油三部 2.92 74\n",
|
|
"物资采购中心 3.17 16\n",
|
|
"科技发展部 3.0 9\n",
|
|
"设备工程部 3.1 19\n",
|
|
"检验计量中心 3.02 39\n",
|
|
"财务资产部 3.4 12\n",
|
|
"党群工作部 3.33 6\n",
|
|
"恒大化工 2.98 39\n",
|
|
"发展计划部 3.23 8\n",
|
|
"安全环保部 2.98 16\n",
|
|
"生产技术部（总调度室） 3.03 17\n",
|
|
"党委组织部（人力资源部） 3.15 12\n",
|
|
"电气仪表中心 2.94 37\n",
|
|
"综合管理部 3.21 14\n",
|
|
"本部 3.34 8\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"depart = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if v['unit'] not in depart:\n",
|
|
" depart.append(v['unit'])\n",
|
|
"\n",
|
|
"for item in depart:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items():\n",
|
|
" if item == v['unit']:\n",
|
|
" score = score + v['score']\n",
|
|
" n = n +1 \n",
|
|
" print(item,round(score/n,2),n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "83ca1488-9b2d-493c-b540-904a5f0af114",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 按照部门计算平均成绩（女性）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"id": "d1977ca9-bf12-4f09-ae7b-e8af9eaa82f2",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:16:38.052997Z",
|
|
"iopub.status.busy": "2024-12-04T15:16:38.052411Z",
|
|
"iopub.status.idle": "2024-12-04T15:16:38.070279Z",
|
|
"shell.execute_reply": "2024-12-04T15:16:38.069338Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:16:38.052942Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"炼油二部 3.17 13\n",
|
|
"公用工程部 3.33 11\n",
|
|
"储运部 2.98 6\n",
|
|
"炼油一部 3.21 15\n",
|
|
"炼油三部 2.82 6\n",
|
|
"物资采购中心 3.05 5\n",
|
|
"科技发展部 2.67 1\n",
|
|
"设备工程部 3.72 2\n",
|
|
"检验计量中心 2.97 19\n",
|
|
"财务资产部 3.46 10\n",
|
|
"党群工作部 3.67 2\n",
|
|
"恒大化工 2.98 26\n",
|
|
"发展计划部 3.61 5\n",
|
|
"安全环保部 3.25 2\n",
|
|
"生产技术部（总调度室） 3.67 1\n",
|
|
"党委组织部（人力资源部） 3.3 7\n",
|
|
"电气仪表中心 3.28 2\n",
|
|
"综合管理部 3.42 7\n",
|
|
"本部 0 0\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"depart = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if v['unit'] not in depart:\n",
|
|
" depart.append(v['unit'])\n",
|
|
"\n",
|
|
"for item in depart:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items():\n",
|
|
" if item == v['unit'] and v['sex'] == '女':\n",
|
|
" score = score + v['score']\n",
|
|
" n = n +1 \n",
|
|
" if n>0:\n",
|
|
" print(item,round(score/n,2),n)\n",
|
|
" else:\n",
|
|
" print(item,0,n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "9f111ad0-dfbe-408e-8652-b8f31fc910cb",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算部门等级"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"id": "d507c7f7-6a91-4695-b700-5e2f77e6dea3",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:17:22.384324Z",
|
|
"iopub.status.busy": "2024-12-04T15:17:22.383584Z",
|
|
"iopub.status.idle": "2024-12-04T15:17:22.404238Z",
|
|
"shell.execute_reply": "2024-12-04T15:17:22.403084Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:17:22.384258Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"炼油二部 14 29 67 26\n",
|
|
"公用工程部 8 11 25 9\n",
|
|
"储运部 8 25 42 26\n",
|
|
"炼油一部 7 27 69 19\n",
|
|
"炼油三部 5 11 43 15\n",
|
|
"物资采购中心 3 3 9 1\n",
|
|
"科技发展部 1 0 7 1\n",
|
|
"设备工程部 2 5 10 2\n",
|
|
"检验计量中心 4 11 18 6\n",
|
|
"财务资产部 3 3 5 1\n",
|
|
"党群工作部 2 1 3 0\n",
|
|
"恒大化工 3 9 20 7\n",
|
|
"发展计划部 1 3 3 1\n",
|
|
"安全环保部 1 5 7 3\n",
|
|
"生产技术部（总调度室） 2 4 9 2\n",
|
|
"党委组织部（人力资源部） 0 5 6 1\n",
|
|
"电气仪表中心 1 9 19 8\n",
|
|
"综合管理部 4 4 4 2\n",
|
|
"本部 1 5 2 0\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"items = ['优秀','良好','合格','不合格'] \n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"\n",
|
|
"dict3 = {}\n",
|
|
"for k, v in dict1.items():\n",
|
|
" unit = v['unit']\n",
|
|
" dict3.setdefault(unit,{})\n",
|
|
" for item in items:\n",
|
|
" dict3[unit].setdefault(item,0)\n",
|
|
"\n",
|
|
"for k, v in dict1.items():\n",
|
|
" unit = v['unit']\n",
|
|
" #dict3.setdefault(unit,{})\n",
|
|
" #for item in items:\n",
|
|
" #dict3[unit].setdefault(v['level'],0)\n",
|
|
" dict3[unit][v['level']] +=1\n",
|
|
"for k, v in dict3.items():\n",
|
|
" print(k,v['优秀'],v['良好'],v['合格'],v['不合格'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6345e3dc-509c-4a6f-8a0a-5c972d6f5828",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算部门成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"id": "90bc66cd-9f01-410e-9abc-e6f15ada293f",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-12-04T15:19:48.512361Z",
|
|
"iopub.status.busy": "2024-12-04T15:19:48.511640Z",
|
|
"iopub.status.idle": "2024-12-04T15:19:48.542915Z",
|
|
"shell.execute_reply": "2024-12-04T15:19:48.542354Z",
|
|
"shell.execute_reply.started": "2024-12-04T15:19:48.512295Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"炼油二部\n",
|
|
"BMI 444 136\n",
|
|
"肺活量 478 134\n",
|
|
"握力 365 136\n",
|
|
"坐位体前屈 345 130\n",
|
|
"纵跳 347 133\n",
|
|
"俯卧撑 352 106\n",
|
|
"一分钟仰卧起坐 50 12\n",
|
|
"单脚站立 356 134\n",
|
|
"选择反应时 432 136\n",
|
|
"台阶指数 284 102\n",
|
|
"公用工程部\n",
|
|
"BMI 199 53\n",
|
|
"肺活量 190 53\n",
|
|
"握力 133 53\n",
|
|
"坐位体前屈 138 51\n",
|
|
"纵跳 127 52\n",
|
|
"俯卧撑 120 39\n",
|
|
"一分钟仰卧起坐 33 9\n",
|
|
"单脚站立 134 53\n",
|
|
"选择反应时 186 53\n",
|
|
"台阶指数 101 38\n",
|
|
"储运部\n",
|
|
"BMI 351 101\n",
|
|
"肺活量 321 99\n",
|
|
"握力 281 101\n",
|
|
"坐位体前屈 245 91\n",
|
|
"纵跳 220 91\n",
|
|
"俯卧撑 238 80\n",
|
|
"一分钟仰卧起坐 10 4\n",
|
|
"单脚站立 237 97\n",
|
|
"选择反应时 324 100\n",
|
|
"台阶指数 163 57\n",
|
|
"炼油一部\n",
|
|
"BMI 408 122\n",
|
|
"肺活量 414 121\n",
|
|
"握力 313 122\n",
|
|
"坐位体前屈 329 117\n",
|
|
"纵跳 298 115\n",
|
|
"俯卧撑 327 97\n",
|
|
"一分钟仰卧起坐 40 10\n",
|
|
"单脚站立 336 120\n",
|
|
"选择反应时 393 122\n",
|
|
"台阶指数 275 97\n",
|
|
"炼油三部\n",
|
|
"BMI 262 74\n",
|
|
"肺活量 246 72\n",
|
|
"握力 186 74\n",
|
|
"坐位体前屈 188 72\n",
|
|
"纵跳 169 70\n",
|
|
"俯卧撑 206 63\n",
|
|
"一分钟仰卧起坐 15 5\n",
|
|
"单脚站立 185 73\n",
|
|
"选择反应时 217 74\n",
|
|
"台阶指数 183 59\n",
|
|
"物资采购中心\n",
|
|
"BMI 60 16\n",
|
|
"肺活量 50 16\n",
|
|
"握力 41 16\n",
|
|
"坐位体前屈 54 16\n",
|
|
"纵跳 45 16\n",
|
|
"俯卧撑 44 11\n",
|
|
"一分钟仰卧起坐 21 5\n",
|
|
"单脚站立 44 16\n",
|
|
"选择反应时 55 16\n",
|
|
"台阶指数 36 14\n",
|
|
"科技发展部\n",
|
|
"BMI 31 9\n",
|
|
"肺活量 30 9\n",
|
|
"握力 23 9\n",
|
|
"坐位体前屈 21 9\n",
|
|
"纵跳 26 9\n",
|
|
"俯卧撑 19 7\n",
|
|
"一分钟仰卧起坐 3 1\n",
|
|
"单脚站立 22 9\n",
|
|
"选择反应时 38 9\n",
|
|
"台阶指数 25 8\n",
|
|
"设备工程部\n",
|
|
"BMI 87 19\n",
|
|
"肺活量 63 19\n",
|
|
"握力 45 19\n",
|
|
"坐位体前屈 49 18\n",
|
|
"纵跳 45 18\n",
|
|
"俯卧撑 50 14\n",
|
|
"一分钟仰卧起坐 9 2\n",
|
|
"单脚站立 54 19\n",
|
|
"选择反应时 64 19\n",
|
|
"台阶指数 32 13\n",
|
|
"检验计量中心\n",
|
|
"BMI 153 39\n",
|
|
"肺活量 124 39\n",
|
|
"握力 80 38\n",
|
|
"坐位体前屈 109 35\n",
|
|
"纵跳 68 32\n",
|
|
"俯卧撑 50 14\n",
|
|
"一分钟仰卧起坐 48 13\n",
|
|
"单脚站立 111 37\n",
|
|
"选择反应时 130 39\n",
|
|
"台阶指数 61 23\n",
|
|
"财务资产部\n",
|
|
"BMI 50 12\n",
|
|
"肺活量 44 12\n",
|
|
"握力 30 12\n",
|
|
"坐位体前屈 33 11\n",
|
|
"纵跳 34 12\n",
|
|
"俯卧撑 7 2\n",
|
|
"一分钟仰卧起坐 22 6\n",
|
|
"单脚站立 51 12\n",
|
|
"选择反应时 42 12\n",
|
|
"台阶指数 16 6\n",
|
|
"党群工作部\n",
|
|
"BMI 28 6\n",
|
|
"肺活量 16 6\n",
|
|
"握力 14 6\n",
|
|
"坐位体前屈 21 6\n",
|
|
"纵跳 17 6\n",
|
|
"俯卧撑 15 4\n",
|
|
"一分钟仰卧起坐 10 2\n",
|
|
"单脚站立 21 6\n",
|
|
"选择反应时 21 6\n",
|
|
"台阶指数 17 6\n",
|
|
"恒大化工\n",
|
|
"BMI 157 39\n",
|
|
"肺活量 121 38\n",
|
|
"握力 89 39\n",
|
|
"坐位体前屈 87 35\n",
|
|
"纵跳 91 34\n",
|
|
"俯卧撑 35 10\n",
|
|
"一分钟仰卧起坐 69 19\n",
|
|
"单脚站立 105 39\n",
|
|
"选择反应时 121 39\n",
|
|
"台阶指数 86 29\n",
|
|
"发展计划部\n",
|
|
"BMI 34 8\n",
|
|
"肺活量 24 8\n",
|
|
"握力 18 8\n",
|
|
"坐位体前屈 24 8\n",
|
|
"纵跳 21 8\n",
|
|
"俯卧撑 6 3\n",
|
|
"一分钟仰卧起坐 22 5\n",
|
|
"单脚站立 29 8\n",
|
|
"选择反应时 30 8\n",
|
|
"台阶指数 18 6\n",
|
|
"安全环保部\n",
|
|
"BMI 50 16\n",
|
|
"肺活量 49 15\n",
|
|
"握力 43 16\n",
|
|
"坐位体前屈 47 16\n",
|
|
"纵跳 41 16\n",
|
|
"俯卧撑 38 12\n",
|
|
"一分钟仰卧起坐 7 2\n",
|
|
"单脚站立 39 16\n",
|
|
"选择反应时 62 16\n",
|
|
"台阶指数 36 13\n",
|
|
"生产技术部（总调度室）\n",
|
|
"BMI 63 17\n",
|
|
"肺活量 56 17\n",
|
|
"握力 46 17\n",
|
|
"坐位体前屈 43 17\n",
|
|
"纵跳 37 16\n",
|
|
"俯卧撑 44 13\n",
|
|
"一分钟仰卧起坐 5 1\n",
|
|
"单脚站立 54 17\n",
|
|
"选择反应时 62 17\n",
|
|
"台阶指数 39 15\n",
|
|
"党委组织部（人力资源部）\n",
|
|
"BMI 44 12\n",
|
|
"肺活量 39 12\n",
|
|
"握力 29 12\n",
|
|
"坐位体前屈 31 11\n",
|
|
"纵跳 23 9\n",
|
|
"俯卧撑 17 5\n",
|
|
"一分钟仰卧起坐 24 6\n",
|
|
"单脚站立 36 11\n",
|
|
"选择反应时 47 12\n",
|
|
"台阶指数 23 9\n",
|
|
"电气仪表中心\n",
|
|
"BMI 145 37\n",
|
|
"肺活量 107 36\n",
|
|
"握力 89 37\n",
|
|
"坐位体前屈 86 35\n",
|
|
"纵跳 92 35\n",
|
|
"俯卧撑 106 30\n",
|
|
"一分钟仰卧起坐 9 2\n",
|
|
"单脚站立 92 37\n",
|
|
"选择反应时 133 37\n",
|
|
"台阶指数 64 28\n",
|
|
"综合管理部\n",
|
|
"BMI 56 14\n",
|
|
"肺活量 49 14\n",
|
|
"握力 31 14\n",
|
|
"坐位体前屈 40 13\n",
|
|
"纵跳 29 12\n",
|
|
"俯卧撑 14 5\n",
|
|
"一分钟仰卧起坐 19 5\n",
|
|
"单脚站立 47 14\n",
|
|
"选择反应时 57 14\n",
|
|
"台阶指数 31 10\n",
|
|
"本部\n",
|
|
"BMI 32 8\n",
|
|
"肺活量 36 8\n",
|
|
"握力 20 8\n",
|
|
"坐位体前屈 18 8\n",
|
|
"纵跳 22 8\n",
|
|
"俯卧撑 34 8\n",
|
|
"一分钟仰卧起坐 0 0\n",
|
|
"单脚站立 27 8\n",
|
|
"选择反应时 30 8\n",
|
|
"台阶指数 19 7\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数'] \n",
|
|
"filename = 'data/data_北海炼化2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"\n",
|
|
"filename = 'data/北海炼化人员2024.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict2 = json.load(fl)\n",
|
|
"dict3 = {}\n",
|
|
"\n",
|
|
"for k, v in dict1.items():\n",
|
|
" unit = v['unit']\n",
|
|
" dict3.setdefault(unit,{})\n",
|
|
" for item in items:\n",
|
|
" dict3[unit].setdefault(item,{})\n",
|
|
" dict3[unit][item].setdefault('score',0)\n",
|
|
" dict3[unit][item].setdefault('count',0)\n",
|
|
" for k1,v1 in v['fits'].items():\n",
|
|
" if k1 in items:\n",
|
|
" dict3[unit][k1]['score']+=v1['score']\n",
|
|
" dict3[unit][k1]['count']+=1\n",
|
|
"\n",
|
|
"for k, v in dict3.items():\n",
|
|
" print(k)\n",
|
|
" for k1, v1 in v.items():\n",
|
|
" print(k1,v1['score'],v1['count'])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "bdb81e20-32ec-4e0e-b2ac-13dac2060068",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"# 问卷数据处理分析"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1485fc89-4fc2-437d-a29e-b4a0aab12aa0",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 常用参数及自定义函数"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6f9768ce-2ef5-4253-9fc6-49dbdcf00a19",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"questions = [\n",
|
|
" [1],\n",
|
|
" [-1, 2],\n",
|
|
" [-1, 2],\n",
|
|
" [-1, 8],\n",
|
|
" [-1, 3],\n",
|
|
" [1],\n",
|
|
" [-1],\n",
|
|
" [-1, 7],\n",
|
|
" [2],\n",
|
|
" [2],\n",
|
|
" [2],\n",
|
|
" [2, 3],\n",
|
|
" [2],\n",
|
|
" [2],\n",
|
|
" [3],\n",
|
|
" [3],\n",
|
|
" [3],\n",
|
|
" [3],\n",
|
|
" [3],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [4],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [5],\n",
|
|
" [6],\n",
|
|
" [6],\n",
|
|
" [6],\n",
|
|
" [6],\n",
|
|
" [6],\n",
|
|
" [6],\n",
|
|
" [7],\n",
|
|
" [7],\n",
|
|
" [7],\n",
|
|
" [7],\n",
|
|
" [7],\n",
|
|
" [7],\n",
|
|
" [8],\n",
|
|
" [8],\n",
|
|
" [8],\n",
|
|
" [8],\n",
|
|
" [8],\n",
|
|
" [8],\n",
|
|
" [9],\n",
|
|
" [9],\n",
|
|
" [9],\n",
|
|
" [9],\n",
|
|
" [9],\n",
|
|
" [9],\n",
|
|
" [9]\n",
|
|
"]\n",
|
|
"\n",
|
|
"kinds = [\n",
|
|
" '平和',\n",
|
|
" '气虚',\n",
|
|
" '阳虚',\n",
|
|
" '阴虚',\n",
|
|
" '痰湿',\n",
|
|
" '湿热',\n",
|
|
" '血瘀',\n",
|
|
" '气郁',\n",
|
|
" '特禀'\n",
|
|
"]\n",
|
|
"\n",
|
|
"def tcm_calc(arr):\n",
|
|
" qa = [8, 8, 7, 8, 8, 6, 7, 7, 7]\n",
|
|
" # 成绩数组\n",
|
|
" s = [0] * 9\n",
|
|
" # 遍历五进制\n",
|
|
" for i in range(len(questions)):\n",
|
|
" m = arr[i] - 1\n",
|
|
" for v in questions[i]:\n",
|
|
" if v < 0:\n",
|
|
" s[-v - 1] += 4 - m\n",
|
|
" else:\n",
|
|
" s[v - 1] += m\n",
|
|
" return [int((v / qa[i]) * 25) for i, v in enumerate(s)]\n",
|
|
"\n",
|
|
"def tcm_kind(score):\n",
|
|
" kind = 0\n",
|
|
" near = False\n",
|
|
" max_kind = 0\n",
|
|
" max_score = 0\n",
|
|
" for i in range(1, 9):\n",
|
|
" if score[i] > max_score:\n",
|
|
" max_kind = i\n",
|
|
" max_score = score[i]\n",
|
|
" if score[0] >= 60 and max_score < 40:\n",
|
|
" if max_score >= 30:\n",
|
|
" near = True\n",
|
|
" kind = max_kind\n",
|
|
" else:\n",
|
|
" kind = max_kind\n",
|
|
" return {\n",
|
|
" \"kind\": kind,\n",
|
|
" \"near\": near\n",
|
|
" }\n",
|
|
"list2 = ['成就感','愉快心境','放松程度','压力应对','体力充沛','情感充沛度']\n",
|
|
"list3 = [[5,7],[7,4],[7,4],[7,4],[8,1],[6,1]] \n",
|
|
"list4 = ['颈椎','胸椎','腰椎','骶尾椎']\n",
|
|
"list5 = [[0,10,10],[10,17,7],[17,24,6],[24,26,2]]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "df2d18e2-d2e4-499e-876a-59d8550a8201",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算中医体质"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1acaf159-637e-4101-9881-f6bb79400136",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"filename = 'data/result_东营工程设计院2024_all.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"i = 1\n",
|
|
"list2 = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if 'tcm' in v.keys():\n",
|
|
" list1 = []\n",
|
|
" tcm =v['tcm']\n",
|
|
" for item in tcm:\n",
|
|
" list1.append(item)\n",
|
|
" score = tcm_calc(list1)\n",
|
|
"\n",
|
|
" result = tcm_kind(score)\n",
|
|
" kind = result['kind']\n",
|
|
" near = result['near']\n",
|
|
" #print(i,k,kinds[kind], near, score)\n",
|
|
" #i+=1\n",
|
|
" list3 = []\n",
|
|
" list3.append(k)\n",
|
|
" list3.append(kinds[kind])\n",
|
|
" list3.append(near)\n",
|
|
" for item in score:\n",
|
|
" list3.append(item)\n",
|
|
" list2.append(list3)\n",
|
|
"print(list2)\n",
|
|
"filename = 'data/东营工程设计院中医情况明细表.xlsx'\n",
|
|
"wb = openpyxl.Workbook()\n",
|
|
"sheet = wb.active\n",
|
|
"\n",
|
|
"for row in list2:\n",
|
|
" sheet.append(row)\n",
|
|
" \n",
|
|
"wb.save(filename)\n",
|
|
"print('ok') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "cfb5661f-fd37-4372-9d22-3708d61680f9",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算心理"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ad3078ac-ae53-4bb4-95bd-387631092bf1",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"list2 = ['成就感','愉快心境','放松程度','压力应对','体力充沛','情感充沛度']\n",
|
|
"list3 = [[5,7],[7,4],[7,4],[7,4],[8,1],[6,1]]\n",
|
|
"qb = [\n",
|
|
" 1, 1, 1, 1, 1,\n",
|
|
" 4, 3, 2, 3, 2, 4, 3,\n",
|
|
" 4, 3, 2, 4, 4, 2, 4,\n",
|
|
" 3, 2, 2, 4, 3, 3, 2,\n",
|
|
" 5, 5, 5, 5, 5, 5, 5, 5,\n",
|
|
" 6, 6, 6, 6, 6, 6\n",
|
|
" ]\n",
|
|
"filename = 'data/result_青海all_2.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k, v in dict1.items():\n",
|
|
" if 'psy' in v.keys():\n",
|
|
" psy=v['psy']\n",
|
|
" for i in range(26,40):\n",
|
|
" new_valve = psy[i]-1\n",
|
|
" psy[i] = new_valve\n",
|
|
" dict3 = {}\n",
|
|
" \n",
|
|
" i = 0\n",
|
|
" for item in qb:\n",
|
|
" dict3.setdefault(item,0)\n",
|
|
" dict3[item] +=psy[i]\n",
|
|
" i+=1\n",
|
|
" print(dict3)\n",
|
|
" print(k)\n",
|
|
" for i in range(0,6):\n",
|
|
" score = int(dict3[i+1]/list3[i][0]/list3[i][1]*100)\n",
|
|
" print(list2[i],score)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "20ef0e26-0f7b-4ee8-8b52-005e2d5ad0d4",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算脊柱"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "122f19fb-3531-4074-94e4-e2afdb8af51a",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"list4 = ['颈椎','胸椎','腰椎','骶尾椎']\n",
|
|
"list5 = [[0,10,10],[10,17,7],[17,24,6],[24,26,2]]\n",
|
|
"filename = 'data/result_青海all_2.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for k, v in dict1.items():\n",
|
|
" if 'spine' in v.keys():\n",
|
|
" spine = v['spine']\n",
|
|
" for i in range(0,4):\n",
|
|
" score = 0\n",
|
|
" for ii in range(list5[i][0],list5[i][1]):\n",
|
|
" score+= spine[ii]\n",
|
|
" print(k,list4[i],int(score/list5[i][2]*100)-100)"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.12.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|