{ "cells": [ { "cell_type": "markdown", "id": "19280f5c-8e34-4a64-8dfb-6353cbf597d2", "metadata": { "tags": [], "toc-hr-collapsed": true }, "source": [ "# 体质检测数据处理" ] }, { "cell_type": "markdown", "id": "112d80f4-607b-41f9-bb30-ac2eb8f52ee2", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "## 基础数据管理" ] }, { "cell_type": "markdown", "id": "9a06725f-248b-44dd-b029-c18e7c0689ee", "metadata": {}, "source": [ "### 体测数据按编号汇总" ] }, { "cell_type": "code", "execution_count": null, "id": "47aa588c-1880-44a8-add0-6fad777065d6", "metadata": {}, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "bh = set()\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "list2 = []\n", "rq = '20240612'\n", "filename = f'data/places_result_{rq}.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", " bh.add(line[2])\n", " \n", "#print(list1)\n", "for result in list1:\n", " user = str(result[2])\n", " \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " \n", " item_name = item[m_item]['name']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[4])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", "print(len(re_ta))\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", "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", "list1 = []\n", "for k, v in re_ta.items():\n", " list2 = []\n", " list2.append(str(k))\n", " for item in items:\n", " if item in v.keys():\n", " list2.append(v[item]['成绩']) \n", " elif item =='name':\n", " list2.append(v[item])\n", " else:\n", " list2.append('') \n", " list1.append(list2)\n", "filename = f'data/长炼医院体测情况表({rq}).xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list1:\n", " sheet.append(row)\n", "wb.save(filename)" ] }, { "cell_type": "markdown", "id": "b7dfd50f-a614-497d-8f0a-fa1e4c89168a", "metadata": {}, "source": [ "### 体测项目标准导入" ] }, { "cell_type": "code", "execution_count": null, "id": "8cd73044-56a8-409b-a873-085feb63af17", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "tcbz ={\n", " 'HeightWeigh':'身高体重',\n", " 'StepExperiment':'台阶指数',\n", " 'Lung':'肺活量',\n", " 'Proneness':'坐位体前屈',\n", " 'PowerfullGrip':'握力',\n", " 'OneMinutePushUp':'一分钟仰卧起坐',\n", " 'PushUp':'俯卧撑',\n", " 'VerticalJump':'纵跳',\n", " 'ReactionTime':'选择反应时',\n", " 'FootStand':'单脚站立'\n", "}\n", "wb = openpyxl.load_workbook('data/体质检测标准.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "dict1 = {}\n", "dict3 = {}\n", "for k, v in tcbz.items():\n", " dict3[v] = k\n", "sheet = wb.active\n", "data1 =list(sheet.values)\n", "del data1[0]\n", "for item in data1:\n", " sex = item[0][6:]\n", " if sex =='男':\n", " age_sex = 'M'+item[0][:5]\n", " else:\n", " age_sex = 'F'+item[0][:5]\n", " dict1.setdefault(age_sex,{})\n", " if item[1] in dict3.keys():\n", " xm = dict3[item[1]]\n", " dict1[age_sex].setdefault(xm,[])\n", " dict1[age_sex][xm].append(item[3]/item[4])\n", "dict2 = {}\n", "#print(dict1)\n", "for k, v in dict1.items():\n", " i1 = int(k[1:3])\n", " i2 = int(k[-2:])\n", " m_sex = k[:1]\n", " for i in range(i1,i2+1):\n", " dict2[m_sex+str(i)] = k\n", "dict3 = {}\n", "dict3['person'] = dict2\n", "dict3['criteria'] = dict1\n", "filename = 'data/体质检测标准.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(dict3, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "c36641d8-c54b-43d2-ad9d-ff4cb72deba9", "metadata": {}, "source": [ "### 身高标准导入" ] }, { "cell_type": "code", "execution_count": null, "id": "2ca52d7b-d77e-452f-98f6-95072a5a1934", "metadata": { "tags": [] }, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "tcbz ={\n", " 'HeightWeigh':'身高体重',\n", " 'StepExperiment':'台阶指数',\n", " 'Lung':'肺活量',\n", " 'Proneness':'坐位体前屈',\n", " 'PowerfullGrip':'握力',\n", " 'OneMinutePushUp':'一分钟仰卧起坐',\n", " 'PushUp':'俯卧撑',\n", " 'VerticalJump':'纵跳',\n", " 'ReactionTime':'选择反应时',\n", " 'FootStand':'单脚站立'\n", "}\n", "wb = openpyxl.load_workbook('data/体质检测标准_BMI.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "dict1 = {}\n", "dict3 = {}\n", "for k, v in tcbz.items():\n", " dict3[v] = k\n", "sheet = wb.active\n", "data1 =list(sheet.values)\n", "del data1[0]\n", "for item in data1:\n", " min_age = int(item[1]/12)\n", " max_age = int((item[2]+1)/12) - 1\n", " sex = item[0]\n", " height = int(item[3])\n", " if sex ==0:\n", " age_sex = 'M'+str(min_age)+'~'+str(max_age)\n", " else:\n", " age_sex = 'F'+str(min_age)+'~'+str(max_age)\n", " dict1.setdefault(age_sex,{})\n", " \n", " dict1[age_sex].setdefault(height,[])\n", " dict1[age_sex][height].append(item[5]/1000)\n", "dict2 = {}\n", "#print(dict1)\n", "for k, v in dict1.items():\n", " i1 = int(k[1:3])\n", " i2 = int(k[-2:])\n", " m_sex = k[:1]\n", " for i in range(i1,i2+1):\n", " dict2[m_sex+str(i)] = k\n", "dict3 = {}\n", "dict3['person'] = dict2\n", "dict3['criteria'] = dict1\n", "filename = 'data/体质检测标准_BMI.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(dict3, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "ad5a702c-1503-463f-9d02-b78b881aad1b", "metadata": {}, "source": [ "### 生成项目信息" ] }, { "cell_type": "code", "execution_count": null, "id": "5071c245-3fdb-4c16-8f15-998af7c1d2fe", "metadata": {}, "outputs": [], "source": [ "import json\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", " del item[k]['divisor']\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/体质检测项目信息.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(item, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "59f5708d-c2d0-4470-b2f4-b9face431865", "metadata": {}, "source": [ "### 计算分数" ] }, { "cell_type": "code", "execution_count": null, "id": "f32b266a-7e46-4703-ab61-7cbbc81b5ab1", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = 'data/体质检测标准.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "person = dict1['person']\n", "criteria = dict1['criteria']\n", "data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46}\n", "info = data['sex']+str(data['age'])\n", "bz = person[info]\n", "mx = criteria[bz][data['item']]\n", "result = data['result']\n", "score = -1\n", "print(mx)\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", "#if score == -1:\n", " # score = 5\n", "print(score)" ] }, { "cell_type": "markdown", "id": "755f8b66-c71c-4138-bd12-dff24e85e36a", "metadata": {}, "source": [ "### 计算BMI分数" ] }, { "cell_type": "code", "execution_count": null, "id": "b32fbbdd-eb0a-4f0d-8901-e39a727c3ff8", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = 'data/体质检测标准_BMI.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "person = dict1['person']\n", "criteria = dict1['criteria']\n", "data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n", "info = data['sex']+str(data['age'])\n", "\n", "bz = person[info]\n", "print(bz)\n", "result = data['result']\n", "print(result)\n", "height = int(float(result.split(',')[0]))\n", "weight = float(result.split(',')[1])\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", "print(score)" ] }, { "cell_type": "markdown", "id": "7fe0ffe8-c3d1-4843-9765-87d4a12b7c39", "metadata": {}, "source": [ "## 体测报告生成" ] }, { "cell_type": "markdown", "id": "9fec0bfc-8a97-446f-95fe-6e9cf8e482d8", "metadata": {}, "source": [ "### 转换报告格式" ] }, { "cell_type": "code", "execution_count": null, "id": "3e614f4a-a623-48e2-97f8-b31f62c9a983", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import datetime\n", "import csv\n", "from datetime import date\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "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", "\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/天津石化人员2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20241104.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", "#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": null, "id": "b123ee6b-85d2-4660-b226-321832a6b796", "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_天津2024（部门）.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "file_path ='./天津石化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'] = '中石化(天津)石油化工\\n有限公司'\n", " mydata['subtitle'] = v['unit']+' '+v['sub_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/中安联合'\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": "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": 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": 36, "id": "63edd636-f034-4aa6-8575-63d5cdb84adb", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T11:54:26.112966Z", "iopub.status.busy": "2024-11-07T11:54:26.112213Z", "iopub.status.idle": "2024-11-07T11:54:26.160290Z", "shell.execute_reply": "2024-11-07T11:54:26.159716Z", "shell.execute_reply.started": "2024-11-07T11:54:26.112896Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "平均成绩：2.4229分，男性：2879人\n", "平均成绩：2.9036分，女性：1180人\n", "平均成绩：2.5627分，总体：4059人\n" ] } ], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "filename = 'data/data_天津石化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": 37, "id": "1b4a3f02-9b2e-41fc-ac6c-8163907a07f1", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T11:56:11.605960Z", "iopub.status.busy": "2024-11-07T11:56:11.605212Z", "iopub.status.idle": "2024-11-07T11:56:11.779109Z", "shell.execute_reply": "2024-11-07T11:56:11.778491Z", "shell.execute_reply.started": "2024-11-07T11:56:11.605889Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0~255分人数：1925人,男性：1627人,女性:298人\n", "256~332分人数：1582人,男性：1007人,女性:575人\n", "333~367分人数：392人,男性：192人,女性:200人\n", "368~500分人数：160人,男性：53人,女性:107人\n", "4059\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": 38, "id": "2d661ca6-6129-4da1-ac25-51d0156babb2", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T11:57:31.108486Z", "iopub.status.busy": "2024-11-07T11:57:31.107793Z", "iopub.status.idle": "2024-11-07T11:57:31.155952Z", "shell.execute_reply": "2024-11-07T11:57:31.155372Z", "shell.execute_reply.started": "2024-11-07T11:57:31.108422Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20-24 {'合格': 105, '不合格': 70, '良好': 20, '优秀': 4}\n", "25-29 {'合格': 70, '不合格': 44, '良好': 18, '优秀': 4}\n", "30-34 {'合格': 26, '不合格': 15, '优秀': 7, '良好': 11}\n", "35-39 {'不合格': 28, '合格': 63, '良好': 26, '优秀': 16}\n", "40-44 {'不合格': 23, '良好': 24, '合格': 47, '优秀': 9}\n", "45-49 {'合格': 156, '不合格': 73, '优秀': 30, '良好': 67}\n", "50-54 {'合格': 108, '不合格': 45, '良好': 34, '优秀': 37}\n", "55-80 {'良好': 0, '不合格': 0, '合格': 0, '优秀': 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": 39, "id": "fc97df37-34ff-4a02-9d26-b5d81b706e46", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T11:59:17.822639Z", "iopub.status.busy": "2024-11-07T11:59:17.821878Z", "iopub.status.idle": "2024-11-07T11:59:17.878973Z", "shell.execute_reply": "2024-11-07T11:59:17.878408Z", "shell.execute_reply.started": "2024-11-07T11:59:17.822567Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20-24 {'合格': 148, '不合格': 264, '良好': 18, '优秀': 4}\n", "25-29 {'合格': 90, '不合格': 181, '良好': 19, '优秀': 3}\n", "30-34 {'合格': 34, '不合格': 68, '优秀': 1, '良好': 6}\n", "35-39 {'不合格': 137, '合格': 95, '良好': 23, '优秀': 5}\n", "40-44 {'不合格': 76, '良好': 24, '合格': 78, '优秀': 7}\n", "45-49 {'合格': 112, '不合格': 185, '优秀': 6, '良好': 24}\n", "50-54 {'合格': 266, '不合格': 407, '良好': 49, '优秀': 19}\n", "55-80 {'良好': 29, '不合格': 309, '合格': 184, '优秀': 8}\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": 40, "id": "dafb86f8-5ee0-4c87-a98f-c7ff0f631fe5", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:00:36.595527Z", "iopub.status.busy": "2024-11-07T12:00:36.594898Z", "iopub.status.idle": "2024-11-07T12:00:36.649736Z", "shell.execute_reply": "2024-11-07T12:00:36.649091Z", "shell.execute_reply.started": "2024-11-07T12:00:36.595465Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "16~24岁平均成绩：2.46分，人数：633人,男性：434人\n", "25~29岁平均成绩：2.48分，人数：429人,男性：293人\n", "30~34岁平均成绩：2.59分，人数：168人,男性：109人\n", "35~39岁平均成绩：2.66分，人数：393人,男性：260人\n", "40~44岁平均成绩：2.75分，人数：288人,男性：185人\n", "45~49岁平均成绩：2.68分，人数：653人,男性：327人\n", "50~54岁平均成绩：2.57分，人数：965人,男性：741人\n", "55~69岁平均成绩：2.4分，人数：530人,男性：530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": 41, "id": "347703a1-501b-4800-bd29-16e94f4a6793", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:02:05.653028Z", "iopub.status.busy": "2024-11-07T12:02:05.651478Z", "iopub.status.idle": "2024-11-07T12:02:05.696252Z", "shell.execute_reply": "2024-11-07T12:02:05.695601Z", "shell.execute_reply.started": "2024-11-07T12:02:05.652939Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20~24岁平均成绩：2.36分，人数：434人\n", "25~29岁平均成绩：2.36分，人数：293人\n", "30~34岁平均成绩：2.38分，人数：109人\n", "35~39岁平均成绩：2.51分，人数：260人\n", "40~44岁平均成绩：2.63分，人数：185人\n", "45~49岁平均成绩：2.41分，人数：327人\n", "50~54岁平均成绩：2.43分，人数：741人\n", "55~80岁平均成绩：2.4分，人数：530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": 42, "id": "5900d1c7-2f8c-4dfa-a60e-a577fb90f22d", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:03:03.848701Z", "iopub.status.busy": "2024-11-07T12:03:03.848001Z", "iopub.status.idle": "2024-11-07T12:03:03.906466Z", "shell.execute_reply": "2024-11-07T12:03:03.905829Z", "shell.execute_reply.started": "2024-11-07T12:03:03.848635Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20~24岁平均成绩：2.69分，人数：199人\n", "25~29岁平均成绩：2.74分，人数：136人\n", "30~34岁平均成绩：2.96分，人数：59人\n", "35~39岁平均成绩：2.97分，人数：133人\n", "40~44岁平均成绩：2.96分，人数：103人\n", "45~49岁平均成绩：2.96分，人数：326人\n", "50~54岁平均成绩：3.03分，人数：224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": 43, "id": "ad69c45d-3f62-42df-894d-47424e759029", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:03:50.847771Z", "iopub.status.busy": "2024-11-07T12:03:50.846994Z", "iopub.status.idle": "2024-11-07T12:03:50.910690Z", "shell.execute_reply": "2024-11-07T12:03:50.910134Z", "shell.execute_reply.started": "2024-11-07T12:03:50.847699Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "BMI 3.4 4044\n", "肺活量 3.09 3995\n", "握力 1.3 4005\n", "坐位体前屈 2.97 3592\n", "纵跳 1.98 3690\n", "俯卧撑 2.22 2160\n", "一分钟仰卧起坐 4.02 771\n", "单脚站立 2.44 3732\n", "选择反应时 2.73 4030\n", "台阶指数 2.76 1547\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": 44, "id": "dcf152e7-bbcc-47d1-9c5f-83854db35412", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:06:22.566290Z", "iopub.status.busy": "2024-11-07T12:06:22.564608Z", "iopub.status.idle": "2024-11-07T12:06:22.615761Z", "shell.execute_reply": "2024-11-07T12:06:22.615219Z", "shell.execute_reply.started": "2024-11-07T12:06:22.566204Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "炼油部 2.48 1131\n", "行政事务中心 2.55 17\n", "烯烃部 2.54 292\n", "党委党校（培训中心） 2.84 29\n", "原油储运部 2.52 198\n", "公司机关 2.64 82\n", "研究院 2.82 89\n", "消防支队 2.61 77\n", "热电部 2.61 366\n", "信息档案管理中心 2.87 54\n", "水务部 2.55 303\n", "化工部 2.57 479\n", "装备研究院 2.92 39\n", "化验计量部 2.65 339\n", "电仪部 2.49 244\n", "物资采购中心 2.79 51\n", "聚醚部 2.76 46\n", "南港烯烃部 2.49 54\n", "运输销售部 2.54 169\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": 48, "id": "d1977ca9-bf12-4f09-ae7b-e8af9eaa82f2", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:15:49.489643Z", "iopub.status.busy": "2024-11-07T12:15:49.488878Z", "iopub.status.idle": "2024-11-07T12:15:49.540929Z", "shell.execute_reply": "2024-11-07T12:15:49.540310Z", "shell.execute_reply.started": "2024-11-07T12:15:49.489570Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "炼油部 2.37 866\n", "行政事务中心 2.48 11\n", "烯烃部 2.38 208\n", "党委党校（培训中心） 2.74 14\n", "原油储运部 2.41 148\n", "公司机关 2.43 45\n", "研究院 2.67 60\n", "消防支队 2.54 64\n", "热电部 2.53 306\n", "信息档案管理中心 2.8 24\n", "水务部 2.4 218\n", "化工部 2.42 327\n", "装备研究院 2.71 21\n", "化验计量部 2.35 149\n", "电仪部 2.4 193\n", "物资采购中心 2.45 23\n", "聚醚部 2.4 27\n", "南港烯烃部 2.4 37\n", "运输销售部 2.43 138\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'] == '男':\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": 47, "id": "d507c7f7-6a91-4695-b700-5e2f77e6dea3", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:14:25.642028Z", "iopub.status.busy": "2024-11-07T12:14:25.641288Z", "iopub.status.idle": "2024-11-07T12:14:25.691163Z", "shell.execute_reply": "2024-11-07T12:14:25.690591Z", "shell.execute_reply.started": "2024-11-07T12:14:25.641958Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "炼油部 27 92 395 617\n", "行政事务中心 1 2 6 8\n", "烯烃部 13 29 107 143\n", "党委党校（培训中心） 3 4 13 9\n", "原油储运部 5 14 78 101\n", "公司机关 2 11 34 35\n", "研究院 7 15 39 28\n", "消防支队 2 10 29 36\n", "热电部 23 47 136 160\n", "信息档案管理中心 1 11 28 14\n", "水务部 15 22 124 142\n", "化工部 20 42 210 207\n", "装备研究院 4 5 19 11\n", "化验计量部 15 36 157 131\n", "电仪部 3 18 91 132\n", "物资采购中心 5 11 16 19\n", "聚醚部 6 5 14 21\n", "南港烯烃部 1 4 20 29\n", "运输销售部 7 14 66 82\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": 49, "id": "90bc66cd-9f01-410e-9abc-e6f15ada293f", "metadata": { "execution": { "iopub.execute_input": "2024-11-07T12:19:03.411081Z", "iopub.status.busy": "2024-11-07T12:19:03.410347Z", "iopub.status.idle": "2024-11-07T12:19:03.485846Z", "shell.execute_reply": "2024-11-07T12:19:03.485281Z", "shell.execute_reply.started": "2024-11-07T12:19:03.411010Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "炼油部\n", "BMI 3704 1128\n", "肺活量 3450 1111\n", "握力 1463 1115\n", "坐位体前屈 2890 1023\n", "纵跳 2119 1040\n", "俯卧撑 1317 686\n", "一分钟仰卧起坐 759 196\n", "单脚站立 2205 1035\n", "选择反应时 3087 1123\n", "台阶指数 1333 482\n", "行政事务中心\n", "BMI 57 17\n", "肺活量 41 16\n", "握力 22 16\n", "坐位体前屈 49 17\n", "纵跳 34 17\n", "俯卧撑 15 9\n", "一分钟仰卧起坐 28 6\n", "单脚站立 35 15\n", "选择反应时 43 17\n", "台阶指数 39 13\n", "烯烃部\n", "BMI 1000 290\n", "肺活量 875 287\n", "握力 387 290\n", "坐位体前屈 737 251\n", "纵跳 508 250\n", "俯卧撑 320 153\n", "一分钟仰卧起坐 215 51\n", "单脚站立 593 271\n", "选择反应时 819 291\n", "台阶指数 312 110\n", "党委党校（培训中心）\n", "BMI 111 29\n", "肺活量 90 26\n", "握力 31 28\n", "坐位体前屈 92 27\n", "纵跳 65 27\n", "俯卧撑 15 10\n", "一分钟仰卧起坐 51 13\n", "单脚站立 74 26\n", "选择反应时 80 28\n", "台阶指数 18 5\n", "原油储运部\n", "BMI 656 198\n", "肺活量 594 196\n", "握力 252 197\n", "坐位体前屈 491 171\n", "纵跳 318 181\n", "俯卧撑 243 108\n", "一分钟仰卧起坐 152 41\n", "单脚站立 462 185\n", "选择反应时 552 197\n", "台阶指数 203 78\n", "公司机关\n", "BMI 314 82\n", "肺活量 262 81\n", "握力 77 82\n", "坐位体前屈 215 74\n", "纵跳 164 80\n", "俯卧撑 91 36\n", "一分钟仰卧起坐 114 28\n", "单脚站立 208 79\n", "选择反应时 210 82\n", "台阶指数 146 53\n", "研究院\n", "BMI 333 89\n", "肺活量 289 86\n", "握力 126 87\n", "坐位体前屈 262 82\n", "纵跳 209 83\n", "俯卧撑 128 53\n", "一分钟仰卧起坐 83 21\n", "单脚站立 223 86\n", "选择反应时 253 89\n", "台阶指数 102 34\n", "消防支队\n", "BMI 273 77\n", "肺活量 212 77\n", "握力 113 77\n", "坐位体前屈 216 70\n", "纵跳 106 73\n", "俯卧撑 149 50\n", "一分钟仰卧起坐 37 9\n", "单脚站立 177 65\n", "选择反应时 234 75\n", "台阶指数 70 28\n", "热电部\n", "BMI 1184 362\n", "肺活量 1148 364\n", "握力 506 361\n", "坐位体前屈 948 312\n", "纵跳 714 330\n", "俯卧撑 551 219\n", "一分钟仰卧起坐 164 40\n", "单脚站立 858 335\n", "选择反应时 1012 366\n", "台阶指数 432 152\n", "信息档案管理中心\n", "BMI 218 54\n", "肺活量 182 53\n", "握力 62 54\n", "坐位体前屈 170 49\n", "纵跳 107 52\n", "俯卧撑 60 23\n", "一分钟仰卧起坐 85 21\n", "单脚站立 155 54\n", "选择反应时 155 54\n", "台阶指数 83 30\n", "水务部\n", "BMI 1017 303\n", "肺活量 883 296\n", "握力 378 298\n", "坐位体前屈 751 256\n", "纵跳 547 276\n", "俯卧撑 383 153\n", "一分钟仰卧起坐 250 61\n", "单脚站立 679 279\n", "选择反应时 822 300\n", "台阶指数 260 99\n", "化工部\n", "BMI 1601 477\n", "肺活量 1437 473\n", "握力 568 468\n", "坐位体前屈 1311 423\n", "纵跳 867 440\n", "俯卧撑 572 249\n", "一分钟仰卧起坐 358 86\n", "单脚站立 1119 443\n", "选择反应时 1271 473\n", "台阶指数 491 166\n", "装备研究院\n", "BMI 167 39\n", "肺活量 124 38\n", "握力 45 38\n", "坐位体前屈 115 38\n", "纵跳 94 36\n", "俯卧撑 39 17\n", "一分钟仰卧起坐 47 11\n", "单脚站立 121 38\n", "选择反应时 102 39\n", "台阶指数 34 12\n", "化验计量部\n", "BMI 1231 339\n", "肺活量 1022 333\n", "握力 435 334\n", "坐位体前屈 901 295\n", "纵跳 519 290\n", "俯卧撑 177 87\n", "一分钟仰卧起坐 329 84\n", "单脚站立 828 299\n", "选择反应时 919 333\n", "台阶指数 228 86\n", "电仪部\n", "BMI 793 243\n", "肺活量 762 240\n", "握力 312 244\n", "坐位体前屈 667 232\n", "纵跳 407 230\n", "俯卧撑 358 153\n", "一分钟仰卧起坐 136 36\n", "单脚站立 617 237\n", "选择反应时 590 244\n", "台阶指数 281 113\n", "物资采购中心\n", "BMI 184 50\n", "肺活量 150 51\n", "握力 62 51\n", "坐位体前屈 128 39\n", "纵跳 101 43\n", "俯卧撑 36 15\n", "一分钟仰卧起坐 90 20\n", "单脚站立 139 43\n", "选择反应时 143 51\n", "台阶指数 49 16\n", "聚醚部\n", "BMI 159 45\n", "肺活量 163 46\n", "握力 67 43\n", "坐位体前屈 125 41\n", "纵跳 84 41\n", "俯卧撑 53 21\n", "一分钟仰卧起坐 61 13\n", "单脚站立 121 44\n", "选择反应时 122 46\n", "台阶指数 49 19\n", "南港烯烃部\n", "BMI 170 54\n", "肺活量 170 54\n", "握力 72 54\n", "坐位体前屈 163 54\n", "纵跳 117 53\n", "俯卧撑 78 32\n", "一分钟仰卧起坐 42 10\n", "单脚站立 124 54\n", "选择反应时 122 54\n", "台阶指数 34 18\n", "运输销售部\n", "BMI 590 168\n", "肺活量 475 167\n", "握力 242 168\n", "坐位体前屈 444 138\n", "纵跳 226 148\n", "俯卧撑 214 86\n", "一分钟仰卧起坐 100 24\n", "单脚站立 353 144\n", "选择反应时 463 168\n", "台阶指数 98 33\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_天津石化2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/天津石化人员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 }