1909 lines
55 KiB
Plaintext
1909 lines
55 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": "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": "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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{
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"cell_type": "markdown",
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"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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{
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"cell_type": "markdown",
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"id": "9fec0bfc-8a97-446f-95fe-6e9cf8e482d8",
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"metadata": {},
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"source": [
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"### 转换报告格式"
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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": 97,
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"id": "3e614f4a-a623-48e2-97f8-b31f62c9a983",
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"metadata": {
|
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"execution": {
|
|
"iopub.execute_input": "2024-01-03T14:02:28.840955Z",
|
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"iopub.status.busy": "2024-01-03T14:02:28.840736Z",
|
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"iopub.status.idle": "2024-01-03T14:02:28.856652Z",
|
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"shell.execute_reply": "2024-01-03T14:02:28.856241Z",
|
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"shell.execute_reply.started": "2024-01-03T14:02:28.840937Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"44\n",
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"44\n"
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]
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}
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],
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"source": [
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"import json\n",
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"import datetime\n",
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"import csv\n",
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"from datetime import date\n",
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"\n",
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"filename = '../item.json'\n",
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"item = {}\n",
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"unit = {}\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"for k,v in dict1.items():\n",
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" item[k] = v\n",
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"item['1']['en'] = 'lung'\n",
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"item['2']['en'] = 'grip'\n",
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"item['3']['en'] = 'flexion'\n",
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"item['4']['en'] = 'jump'\n",
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"item['5']['en'] = 'pushup'\n",
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"item['6']['en'] = 'balance'\n",
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"item['7']['en'] = 'reaction'\n",
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"item['8']['en'] = 'step'\n",
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"item['9']['en'] = 'situp'\n",
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"item['10']['en'] = 'height'\n",
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"item['11']['en'] = 'weight'\n",
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"\n",
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"\n",
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"re_ta = {}\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"filename = 'data/中国石化化工销售.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_20240103.csv'\n",
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
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" for line in fl:\n",
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" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
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" list1.append(line)\n",
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"#f_item = ['lung','grip','flexion','jump','balance','reaction','step','situp']\n",
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"#m_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
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"for result in list1:\n",
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" user = str(result[2])\n",
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" rq = date.fromisoformat(result[6].replace('/','-'))\n",
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" if user in dict1.keys():\n",
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" l_xm = []\n",
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" m_item = str(result[3]) \n",
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" re_ta.setdefault(user,{}) \n",
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" re_ta[user]['name'] = dict1[user]['name']\n",
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" re_ta[user]['sex'] = dict1[user]['sex']\n",
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" if dict1[user]['sex'] == '男':\n",
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" l_xm = ['weight','height','lung','grip','flexion','jump','pushup','balance','reaction','step']\n",
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" else:\n",
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" l_xm = ['weight','height','lung','grip','flexion','jump','balance','reaction','step','situp']\n",
|
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" re_ta[user]['unit'] = dict1[user]['unit']\n",
|
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" #birth = date.fromisoformat(dict1[user]['birth'].replace('/','-'))\n",
|
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" birth = date.fromisoformat(dict1[user]['birth'])\n",
|
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" #nian = int(birth[0].strip())\n",
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" #yue = int(birth[1].strip())\n",
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" #ri = int(birth[2].strip())\n",
|
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" #print(k,nian,yue,ri)\n",
|
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" item_name = item[m_item]['en'] \n",
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" if item_name in l_xm: \n",
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" days = (rq-birth).days \n",
|
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" re_ta[user]['age'] = int(days/365)\n",
|
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" re_ta[user]['month'] = int(days/365*12)\n",
|
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" re_ta[user]['rq'] = result[6]\n",
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"\n",
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"\n",
|
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" re_ta[user].setdefault(item_name,{}) \n",
|
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" score = int(result[4])/item[m_item]['divisor'] \n",
|
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" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
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"print(len(re_ta))\n",
|
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"filename = 'data/result_中国石化化工销售.json'\n",
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"\n",
|
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"with open(filename,'w') as fl:\n",
|
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" json.dump(re_ta, fl, ensure_ascii=False) \n",
|
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"print(len(re_ta))"
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]
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},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6741916c-deb6-496f-bc8f-5248e107e0e9",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 生成完善得分"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 98,
|
|
"id": "141b30dc-5975-4dcb-9bc3-9b20d26a0917",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-01-03T14:03:22.531744Z",
|
|
"iopub.status.busy": "2024-01-03T14:03:22.531496Z",
|
|
"iopub.status.idle": "2024-01-03T14:03:22.548680Z",
|
|
"shell.execute_reply": "2024-01-03T14:03:22.548172Z",
|
|
"shell.execute_reply.started": "2024-01-03T14:03:22.531714Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"ok!\n"
|
|
]
|
|
}
|
|
],
|
|
"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",
|
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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",
|
|
"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",
|
|
"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_中国石化化工销售.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_中国石化化工销售.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": 100,
|
|
"id": "b123ee6b-85d2-4660-b226-321832a6b796",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2024-01-03T15:42:44.653385Z",
|
|
"iopub.status.busy": "2024-01-03T15:42:44.652940Z",
|
|
"iopub.status.idle": "2024-01-03T15:42:59.566347Z",
|
|
"shell.execute_reply": "2024-01-03T15:42:59.565824Z",
|
|
"shell.execute_reply.started": "2024-01-03T15:42:44.653349Z"
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"43\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_中国石化化工销售.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl)\n",
|
|
"list1 = []\n",
|
|
"fiie_path ='./中国石化化工销售/'\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'] = fiie_path+id+'-'+ v['name']+'.pdf'\n",
|
|
" mydata['title'] = '中国石化化工销售'\n",
|
|
" mydata['subtitle'] = v['unit']\n",
|
|
" mydata['id'] = id\n",
|
|
" mydata['name'] = v['name']\n",
|
|
" if v['sex'] == '男':\n",
|
|
" mydata['gender'] = 'male'\n",
|
|
" else:\n",
|
|
" mydata['gender'] = 'female'\n",
|
|
" \n",
|
|
" mydata['month'] = v['month']\n",
|
|
" mydata['fits'] = {}\n",
|
|
" survey_list = ['tcm','psy','spine']\n",
|
|
" for item in survey_list:\n",
|
|
" if item in v.keys():\n",
|
|
" mydata.setdefault('surveys',{})\n",
|
|
" mydata['surveys'][item] = v[item]\n",
|
|
" \n",
|
|
" \n",
|
|
" #mydata['fits'] = {}\n",
|
|
" for item in list_item:\n",
|
|
" if item in v.keys():\n",
|
|
" mydata.setdefault('fits',{})\n",
|
|
" if item in ['lung','pushup','step','situp']:\n",
|
|
" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
|
|
" else:\n",
|
|
" mark = v[item]['成绩'].split()[0]\n",
|
|
" mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n",
|
|
" #if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n",
|
|
" if len(mydata['fits']) >2 : \n",
|
|
" list1.append(mydata)\n",
|
|
" list2.append([k,v['name']])\n",
|
|
" i+=1\n",
|
|
" x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n",
|
|
" #print(id,v['name'],x.text)\n",
|
|
" #print(mydata)\n",
|
|
" #x.close()\n",
|
|
"print(i)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "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/北海炼化2023'\n",
|
|
"new_path = 'file/北海炼化2023'\n",
|
|
"old = []\n",
|
|
"dict2 = {}\n",
|
|
"\n",
|
|
"filename = 'data/北海炼化2023年.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2023'\n",
|
|
"\n",
|
|
"filename = 'data/北海炼化2023年.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/北海炼化体测报告打印明细表.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": "code",
|
|
"execution_count": null,
|
|
"id": "849ccf0c-374c-4915-98ae-78156203ed59",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"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": null,
|
|
"id": "46aa847d-e1fe-45bd-85b6-e2d792ec8842",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"import openpyxl\n",
|
|
"\n",
|
|
"\n",
|
|
"filename = 'data/result_北海炼化2023.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_北海炼化2023.json'\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict2,fl , ensure_ascii=False) \n",
|
|
"print('ok!') "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "ed5f157a-3114-4221-907d-53ce62409d83",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 计算平均成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "63edd636-f034-4aa6-8575-63d5cdb84adb",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"filename = 'data/data_长炼医院.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": null,
|
|
"id": "1b4a3f02-9b2e-41fc-ac6c-8163907a07f1",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
|
"\n",
|
|
"filename = 'data/data_长炼医院.json'\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"\n",
|
|
"for k1, v1 in dict2.items():\n",
|
|
" di = v1[0]\n",
|
|
" gao = v1[1]\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if int(v['score']*100) in range(di,gao+1):\n",
|
|
" dict1[k]['level'] = k1\n",
|
|
" i+=1\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" else:\n",
|
|
" f = f+1\n",
|
|
" print(f'{di}~{gao}分人数：{i}人,男性：{m}人,女性:{f}人')\n",
|
|
"print(len(dict1))\n",
|
|
"with open(filename,'w') as fl:\n",
|
|
" json.dump(dict1, fl) \n",
|
|
"print('ok')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "39a1239d-13d8-4583-a163-e6db98c3933b",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各年龄段测试等级(女）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2d661ca6-6129-4da1-ac25-51d0156babb2",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"dict3 = {}\n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" age = f'{di}-{gao}'\n",
|
|
" dict3.setdefault(age,{})\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1): \n",
|
|
" dict3[age].setdefault(v['level'],0)\n",
|
|
" if v['sex'] == '女':\n",
|
|
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
|
|
" \n",
|
|
"for k, v in dict3.items():\n",
|
|
" print(k,v)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "b7d10bef-405f-49a1-b423-2b972b4d1a44",
|
|
"metadata": {},
|
|
"source": [
|
|
"### 计算各年龄段测试等级(男）"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "fc97df37-34ff-4a02-9d26-b5d81b706e46",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"dict2 = {}\n",
|
|
"dict2['不合格'] = [0,255]\n",
|
|
"dict2['合格'] = [256,332]\n",
|
|
"dict2['良好'] = [333,367]\n",
|
|
"dict2['优秀'] = [368,500]\n",
|
|
"dict3 = {}\n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" age = f'{di}-{gao}'\n",
|
|
" dict3.setdefault(age,{})\n",
|
|
" i = 0 \n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1): \n",
|
|
" dict3[age].setdefault(v['level'],0)\n",
|
|
" if v['sex'] == '男':\n",
|
|
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
|
|
" \n",
|
|
"for k, v in dict3.items():\n",
|
|
" print(k,v)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "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": null,
|
|
"id": "dafb86f8-5ee0-4c87-a98f-c7ff0f631fe5",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[16,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1):\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if v['sex'] == '男':\n",
|
|
" m = m +1\n",
|
|
" if i ==0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：0分，人数：0人,男性：{m}人')\n",
|
|
" else:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人,男性：{m}人')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "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": null,
|
|
"id": "347703a1-501b-4800-bd29-16e94f4a6793",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import json\n",
|
|
"\n",
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"for item in nld:\n",
|
|
" di = item[0]\n",
|
|
" gao = item[1]\n",
|
|
" i = 0\n",
|
|
" score = 0\n",
|
|
" m = 0\n",
|
|
" f = 0\n",
|
|
" for k,v in dict1.items():\n",
|
|
" if v['age'] in range(di,gao+1) and v['sex'] == '男':\n",
|
|
" score = score+v['score']\n",
|
|
" i+=1\n",
|
|
" if i ==0:\n",
|
|
" print(f'{di}~{gao}岁平均成绩：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": null,
|
|
"id": "5900d1c7-2f8c-4dfa-a60e-a577fb90f22d",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
|
"\n",
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"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": null,
|
|
"id": "ad69c45d-3f62-42df-894d-47424e759029",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
|
"for item in items:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items(): \n",
|
|
" if item in v['fits'].keys():\n",
|
|
" n = n + 1\n",
|
|
" score =score + int(v['fits'][item]['score'])\n",
|
|
" print(item,round(score/n,2),n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "f005328b-1927-4f62-b530-e7750299c423",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 按照部门计算平均成绩"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "dcf152e7-bbcc-47d1-9c5f-83854db35412",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"with open(filename,'r') as fl:\n",
|
|
" dict1 = json.load(fl) \n",
|
|
"depart = []\n",
|
|
"for k, v in dict1.items():\n",
|
|
" if v['unit'] not in depart:\n",
|
|
" depart.append(v['unit'])\n",
|
|
"\n",
|
|
"for item in depart:\n",
|
|
" score = 0\n",
|
|
" n = 0\n",
|
|
" for k, v in dict1.items():\n",
|
|
" if item == v['unit']:\n",
|
|
" score = score + v['score']\n",
|
|
" n = n +1 \n",
|
|
" print(item,round(score/n,2),n)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "46997480-54dd-440f-83a1-0e946d7463f7",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d1977ca9-bf12-4f09-ae7b-e8af9eaa82f2",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "bdb81e20-32ec-4e0e-b2ac-13dac2060068",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"source": [
|
|
"# 体质报告在线管理"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1485fc89-4fc2-437d-a29e-b4a0aab12aa0",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 新增体测单位"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "cf345bf0-f11b-459e-9b69-b2843836f6f3",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import pymongo\n",
|
|
"\n",
|
|
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
|
|
"mydb = myclient[\"baogao\"]\n",
|
|
"mycol = mydb[\"place\"]\n",
|
|
"\n",
|
|
"mydict = { \"id\": \"469849\",\"name\": \"长炼医院\", }\n",
|
|
" \n",
|
|
"x = mycol.insert_one(mydict) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "df2d18e2-d2e4-499e-876a-59d8550a8201",
|
|
"metadata": {},
|
|
"source": [
|
|
"## 新增报告信息"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1acaf159-637e-4101-9881-f6bb79400136",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import pymongo\n",
|
|
"\n",
|
|
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
|
|
"mydb = myclient[\"baogao\"]\n",
|
|
"mycol = mydb[\"pdf\"]\n",
|
|
"\n",
|
|
"mydict = { \"place\": \"714309\",\"code\":\"4\",\"name\": \"朱维\", }\n",
|
|
" \n",
|
|
"x = mycol.insert_one(mydict) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ad3078ac-ae53-4bb4-95bd-387631092bf1",
|
|
"metadata": {
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"import pymongo\n",
|
|
"\n",
|
|
"myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n",
|
|
"mydb = myclient[\"baogao\"]\n",
|
|
"mycol = mydb[\"pdf\"]\n",
|
|
"\n",
|
|
"mydict = { \"place\": \"714309\",\"code\":\"4\",\"name\": \"朱维\", }\n",
|
|
" \n",
|
|
"x = mycol.find_one(mydict) \n",
|
|
"print(x)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "cc0571b6-1da5-4bcc-96ad-5613cd1198e3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.10.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|