{ "cells": [ { "cell_type": "markdown", "id": "92891af2-e909-4b8e-a08a-b5b5e4a1c732", "metadata": {}, "source": [ "# 体质测试" ] }, { "cell_type": "markdown", "id": "338fb8da-815a-4536-ae91-4f461ba9401f", "metadata": {}, "source": [ "## 体测人员导入" ] }, { "cell_type": "code", "execution_count": null, "id": "ba24132c-133f-4508-8fe7-e68d1908b6e9", "metadata": {}, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "from datetime import date\n", "\n", "wb = openpyxl.load_workbook('data/镇海体质监测报名.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(2, sheet.max_row+1):\n", " code = int(sheet.cell(n, 1).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 2).value\n", " dict1['sex'] = sheet.cell(n, 3).value\n", " dict1['unit'] = sheet.cell(n, 7).value\n", " if sheet.cell(n, 5).value is not None:\n", " dict1['gh'] = sheet.cell(n, 5).value\n", " dict1['birth'] = str(sheet.cell(n, 6).value).replace('/','-').split(' ')[0] \n", " if sheet.cell(n, 4).value is not None:\n", " dict1['phone'] = str(sheet.cell(n,4).value)\n", " person[code] = dict1\n", "filename = 'data/镇海.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "10ddfd3b-697c-4459-8bed-147b22f88239", "metadata": {}, "source": [ "## 生成读卡系统文件" ] }, { "cell_type": "code", "execution_count": null, "id": "63ab2d5b-3a0a-4ac7-a3e7-b3a34e621e98", "metadata": {}, "outputs": [], "source": [ "import json\n", "\n", "filename = 'data/镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "for k, v in dict1.items():\n", " dict2 = {}\n", " #if dict1['sex'] =='男':\n", " # sex = 1\n", " \n", " dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n", " list1.append(dict2)\n", "json_data = json.dumps(list1,ensure_ascii=False, indent=4) \n", "\n", "# 将 json 数据写入文件\n", "with open(\"data/data_镇海.json\", \"w\",encoding = 'utf-8') as file:\n", " file.write(json_data) \n", "print('ok')" ] }, { "cell_type": "markdown", "id": "b6dd08b0-f58c-4dc1-86a9-e7b2b84478c3", "metadata": {}, "source": [ "## 获取人员测试成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "5d864909-d10f-461d-8e6e-dc5c43613576", "metadata": {}, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "filename = 'data/镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20240922.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl) \n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append(line)\n", "#print(list1)\n", "for result in list1:\n", " user = str(result[2])\n", " if user in dict1.keys(): \n", " m_item = str(result[3]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = dict1[user]['name']\n", " re_ta[user]['sex'] = dict1[user]['sex'] \n", " re_ta[user]['unit'] = dict1[user]['unit']\n", " #re_ta[user]['sub_unit'] = dict1[user]['sub_unit']\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", "filename = 'data/result_镇海.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": "a08c6b65-a390-451b-b1a5-fc474db40035", "metadata": {}, "source": [ "## 导出测试人员信息" ] }, { "cell_type": "code", "execution_count": 108, "id": "bc79f0d2-62a2-40c8-bd74-9c7ff17bec8e", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T06:59:45.541438Z", "iopub.status.busy": "2024-09-30T06:59:45.540672Z", "iopub.status.idle": "2024-09-30T06:59:46.017490Z", "shell.execute_reply": "2024-09-30T06:59:46.016942Z", "shell.execute_reply.started": "2024-09-30T06:59:45.541365Z" } }, "outputs": [], "source": [ "import json\n", "import openpyxl\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','姓名','性别','单位','部门','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", "\n", "filename = 'data/result_镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/镇海体测人员.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", " \n", "list1 = []\n", "for k, v in dict1.items():\n", " list2 = []\n", " list2.append(str(k).rjust(5,'0'))\n", " list2.append(v['name']) \n", " list2.append(dict2[k]['sex'])\n", " list2.append(dict2[k]['unit']) \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", " list2.append(dict2[k]['gwxl'])\n", " list2.append(dict2[k]['gzz'])\n", " list1.append(list2)\n", "filename = 'data/镇海体测情况表.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)" ] }, { "cell_type": "markdown", "id": "0c2dfa71-8680-4ec6-938d-d37eeba4d4f9", "metadata": {}, "source": [ "## 统计未体测人员明细表" ] }, { "cell_type": "code", "execution_count": null, "id": "cf22739a-5cf3-47fd-b87a-158a2e2d5a95", "metadata": {}, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'data/result_镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/镇海1.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "\n", "list1 = []\n", "\n", "i = 1\n", "for k, v in dict2.items(): \n", " if k not in dict1.keys():\n", " list2 = [i,k,v['name'],v['unit']]\n", " i+=1\n", " list1.append(list2)\n", "#print(list1)\n", "filename = f'data/镇海未测试人员名单（截至20240922）.xlsx'\n", "title = ['序号','员工编号','姓名','部门']\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": "286a65eb-995f-4183-a4e5-6d907ba21151", "metadata": {}, "source": [ "## 清理重复人员" ] }, { "cell_type": "code", "execution_count": null, "id": "f4dade65-f760-4220-8a65-39843688a60a", "metadata": {}, "outputs": [], "source": [ "import json\n", "\n", "filename = 'data/镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "print(len(dict1))\n", "dict2 = {}\n", "for k, v in dict1.items():\n", " if 'phone' in v.keys():\n", " dict2.setdefault(k,{})\n", " dict2[k]['name'] = v['name']\n", " dict2[k]['phone'] = v['phone']\n", "\n", "list1 = []\n", "for k, v in dict2.items():\n", " i = 0\n", " for k1, v1 in dict1.items():\n", " if v['name']== v1['name'] and v['phone'] == v1['phone'] and k1 != k:\n", " list1.append(max(int(k),int(k1)))\n", "for item in set(list1):\n", " del dict1[str(item)]\n", "print(len(dict1))\n", "filename = 'data/镇海1.json'\n", "\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n" ] }, { "cell_type": "markdown", "id": "e513b5bb-8a4e-412a-880b-1ae36e059bfd", "metadata": {}, "source": [ "## 转换报告格式" ] }, { "cell_type": "code", "execution_count": null, "id": "7f038e8d-dd57-4880-8726-6dfa86fbc4a2", "metadata": {}, "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/镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "\n", "filename = 'data/places_result_20240922.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_镇海1.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": "de2eec6d-a74e-47e1-ab7a-c7f6eda80a20", "metadata": {}, "source": [ "## 生成完善得分" ] }, { "cell_type": "code", "execution_count": null, "id": "763aa68a-da54-4745-a759-4399aba10f7e", "metadata": {}, "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_镇海1.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_镇海2.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "723ae3d7-ec16-4dc6-91e2-eeeea6ffe081", "metadata": {}, "source": [ "## 生成报告" ] }, { "cell_type": "code", "execution_count": null, "id": "90faac13-492d-4b3d-bb21-c228af6d9864", "metadata": {}, "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_镇海2.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "file_path ='./镇海石化/'\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n", "i=0\n", "list2 = []\n", "for k, v in dict1.items():\n", " list1 = []\n", " mydata = {}\n", " \n", " id = str(k).rjust(4,\"0\")\n", " mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n", " mydata['title'] = '中国石化镇海炼化公司'\n", " mydata['subtitle'] = v['unit']\n", " mydata['id'] = id\n", " mydata['name'] = v['name']\n", " if v['sex'] == '男':\n", " mydata['gender'] = 'male'\n", " else:\n", " mydata['gender'] = 'female'\n", " \n", " mydata['month'] = v['month']\n", " mydata['fits'] = {}\n", " survey_list = ['tcm','psy','spine']\n", " for item in survey_list:\n", " if item in v.keys():\n", " mydata.setdefault('surveys',{})\n", " mydata['surveys'][item] = v[item]\n", " \n", " \n", " #mydata['fits'] = {}\n", " for item in list_item:\n", " if item in v.keys():\n", " mydata.setdefault('fits',{})\n", " if item in ['lung','pushup','step','situp']:\n", " mark = v[item]['成绩'].split()[0].split('.')[0]\n", " else:\n", " mark = v[item]['成绩'].split()[0]\n", " mydata['fits'][item] = {'mark':mark,'score':v[item]['score']}\n", " #if len(mydata['fits']) >2 or len(mydata['surveys']) >0:\n", " if len(mydata['fits']) >2 : \n", " list1.append(mydata)\n", " list2.append([k,v['name']])\n", " i+=1\n", " x = requests.post('http://localhost:3003', data = json.dumps(list1), headers=headers)\n", " #print(id,v['name'],x.text)\n", " #print(mydata)\n", " #x.close()\n", "print(i)" ] }, { "cell_type": "markdown", "id": "82c1eaea-89ad-444a-8dad-07f438c739cc", "metadata": {}, "source": [ "## 统计报告人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "61c731bc-6117-4a9f-8bfa-66f820e49fc4", "metadata": {}, "outputs": [], "source": [ "import json\n", "import glob\n", "from pathlib import Path\n", "import openpyxl\n", "\n", "filename = 'data/镇海.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "fi_path = '/home/songyi/python/mycrm/flask/pdf/files/345321'\n", "fls = glob.glob(f'{fi_path}/*.pdf')\n", "dict2 = {}\n", "for fn in fls:\n", " \n", " fi_name =Path(fn).stem.split('-')[0]\n", " #fi_name =Path(fn).stem\n", " code = int(fi_name)\n", " dict2[str(code)] = dict1[str(code)]\n", "filename = 'data/镇海体测人员.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print(len(dict2)) \n", "list1 = []\n", "for k, v in dict2.items(): \n", " list2 = []\n", " if 'gh' in v.keys():\n", " gh = v['gh']\n", " else:\n", " gh = ''\n", " if 'phone' in v.keys():\n", " phone = v['phone']\n", " else:\n", " phone = ''\n", " list2 = [k,v['name'],v['sex'],v['birth'],v['unit'],gh,phone]\n", " list1.append(list2)\n", "#print(list1)\n", "filename = 'data/镇海参加测试人员名单.xlsx'\n", "title = ['序号','员工编号','姓名','部门']\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": "fc0f353c-1021-4c8c-bb7c-7a4abb609836", "metadata": {}, "source": [ "## 补充报告人员信息" ] }, { "cell_type": "code", "execution_count": 107, "id": "fa963fb6-b47d-4b75-9109-6cda89218182", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T06:58:38.490350Z", "iopub.status.busy": "2024-09-30T06:58:38.489677Z", "iopub.status.idle": "2024-09-30T06:58:38.708672Z", "shell.execute_reply": "2024-09-30T06:58:38.708145Z", "shell.execute_reply.started": "2024-09-30T06:58:38.490289Z" }, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok!\n" ] } ], "source": [ "import json\n", "import glob\n", "from pathlib import Path\n", "import openpyxl\n", "\n", "\n", "filename = 'data/镇海体测人员.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "wb = openpyxl.load_workbook('data/镇海炼化参加测试人员名单（分析用）.xlsx')\n", "sheet = wb.active\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n, 12).value is not None:\n", " code = int(sheet.cell(n, 1).value)\n", " if sheet.cell(n, 12).value is not None:\n", " dict1[str(code)]['gwlb'] = sheet.cell(n, 12).value\n", " dict1[str(code)]['gwxl'] = sheet.cell(n, 9).value\n", " dict1[str(code)]['gzz'] = sheet.cell(n, 11).value\n", "\n", "with open(filename, 'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print('ok!') \n" ] }, { "cell_type": "markdown", "id": "385285b8-fdb3-421d-afbf-c13e4f55bb46", "metadata": {}, "source": [ "## 核验报告人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "c6195bc3-64bc-4f52-8ebc-ba16fd222f85", "metadata": {}, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "from datetime import date\n", "\n", "wb = openpyxl.load_workbook('data/镇海炼化参加测试人员名单.xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "\n", "for n in range(2, sheet.max_row+1):\n", " code = int(sheet.cell(n, 1).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 2).value\n", " dict1['sex'] = sheet.cell(n, 3).value\n", " dict1['unit'] = sheet.cell(n, 5).value\n", " if sheet.cell(n, 6).value is not None:\n", " dict1['gh'] = sheet.cell(n, 6).value\n", " dict1['birth'] = str(sheet.cell(n, 4).value).replace('/','-').split(' ')[0] \n", " if sheet.cell(n, 7).value is not None:\n", " dict1['phone'] = str(sheet.cell(n,7).value)\n", " if len(str(sheet.cell(n,7).value))<11:\n", " print(code,sheet.cell(n, 2).value)\n", " person[code] = dict1\n", "filename = 'data/镇海炼化参加测试人员.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print(len(person))" ] }, { "cell_type": "markdown", "id": "7e551660-e85f-4da2-8224-042784033ed5", "metadata": {}, "source": [ "## 生成查询信息" ] }, { "cell_type": "code", "execution_count": null, "id": "299c1d41-7634-4703-8411-08f175df4e16", "metadata": {}, "outputs": [], "source": [ "import openpyxl\n", "import os,sys,shutil\n", "import json\n", "import math\n", "import glob\n", "import random\n", "from pathlib import Path\n", "import pymongo\n", "\n", "myclient = pymongo.MongoClient('mongodb://localhost:27017/')\n", "mydb = myclient[\"baogao\"]\n", "mycol = mydb[\"pdf\"]\n", "\n", "place_id = 345321\n", "\n", "fi_path = '/home/songyi/python/mycrm/flask/pdf/files'\n", "fls = glob.glob(f'{fi_path}/{str(place_id)}/*.pdf')\n", "\n", "filename = 'data/镇海炼化参加测试人员.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "for fn in fls:\n", " dict2 = {}\n", " fi_name =Path(fn).stem.split('-')[0]\n", " #fi_name =Path(fn).stem\n", " code = int(fi_name)\n", " dxm = dict1[str(code)]['gh']\n", " dict2 = {'place_id':place_id,'code':dxm,'fn':Path(fn).name}\n", " list2.append(dict2)\n", " i +=1\n", "x = mycol.insert_many(list2)\n", "print('ok') " ] }, { "cell_type": "markdown", "id": "e923022e-aef7-4c8e-84f9-b853e53ff820", "metadata": {}, "source": [ "## 根据工号生成查询信息" ] }, { "cell_type": "code", "execution_count": null, "id": "f709fd4a-d0b0-44a9-a782-0c1ffd43f6b8", "metadata": {}, "outputs": [], "source": [ "import json\n", "filename = 'data/镇海炼化参加测试人员.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "list2 = []\n", "set1 = set()\n", "for k, v in dict1.items():\n", " if 'gh' in v.keys():\n", " gh = v['gh']\n", " if gh not in list1:\n", " list1.append(v['gh'])\n", " else:\n", " list2.append(gh)\n", "print(list2)" ] }, { "cell_type": "markdown", "id": "d9464f81-9228-403a-9d78-090fb4ce0faa", "metadata": {}, "source": [ "## 体测报告按部门分类" ] }, { "cell_type": "code", "execution_count": null, "id": "7eac364f-0fde-4853-9d2b-8c4c0c59a341", "metadata": {}, "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/镇海石化'\n", "new_path = 'file/镇海石化'\n", "old = []\n", "dict2 = {}\n", "\n", "filename = 'data/镇海炼化参加测试人员.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": "d7bb270c-cc9e-413b-af36-17c33692e289", "metadata": {}, "source": [ "## 生成体测报告打印明细表" ] }, { "cell_type": "code", "execution_count": null, "id": "d88bd5c4-1df3-457b-b65d-61692c45e7bd", "metadata": {}, "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/镇海石化'\n", "\n", "filename = 'data/镇海炼化参加测试人员.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/镇海石化体测报告明细表.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list1:\n", " sheet.append(row)\n", " \n", "wb.save(filename) \n", "print('ok')" ] }, { "cell_type": "markdown", "id": "6b521daf-f9dc-4579-9400-d8ab857bb166", "metadata": {}, "source": [ "# 体质测试综合报告数据分析" ] }, { "cell_type": "markdown", "id": "83203d08-46ca-45f6-8204-0c8e35f754b6", "metadata": {}, "source": [ "## 清理报告数据" ] }, { "cell_type": "code", "execution_count": null, "id": "cccc2e43-7a73-48ec-8540-06b4d59f8ceb", "metadata": {}, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "\n", "filename = 'data/result_镇海2.json'\n", "with open(filename,'r',encoding = 'utf-8') 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_镇海.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "1c0bca93-d8a7-42ba-9a2c-50d3493c802f", "metadata": {}, "source": [ "## 报告按照工作制分类" ] }, { "cell_type": "code", "execution_count": 113, "id": "a550ecd7-da8e-41b6-8b8f-8bc144d48bfe", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T07:33:01.527422Z", "iopub.status.busy": "2024-09-30T07:33:01.527168Z", "iopub.status.idle": "2024-09-30T07:33:01.595828Z", "shell.execute_reply": "2024-09-30T07:33:01.595271Z", "shell.execute_reply.started": "2024-09-30T07:33:01.527399Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "782\n" ] } ], "source": [ "import json\n", "import openpyxl\n", "\n", "\n", "filename = 'data/result_镇海2.json'\n", "with open(filename,'r',encoding = 'utf-8') as fl:\n", " dict1 = json.load(fl)\n", "filename = 'data/镇海体测人员.json'\n", "with open(filename,'r',encoding = 'utf-8') as fl:\n", " dict3 = 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", " if dict3[k]['gzz'] == '倒班':\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_镇海_倒班.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict2,fl , ensure_ascii=False) \n", "print(len(dict2)) " ] }, { "cell_type": "markdown", "id": "c3bcd7ec-1d66-40c6-a27d-1c73e6eef695", "metadata": {}, "source": [ "## 计算平均成绩" ] }, { "cell_type": "code", "execution_count": 137, "id": "d5721244-b5f5-4577-bae8-2e6c5bd8e4da", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:09:20.461987Z", "iopub.status.busy": "2024-09-30T08:09:20.460968Z", "iopub.status.idle": "2024-09-30T08:09:20.476548Z", "shell.execute_reply": "2024-09-30T08:09:20.475718Z", "shell.execute_reply.started": "2024-09-30T08:09:20.461927Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "平均成绩：3.2405分，男性：313人\n", "平均成绩：3.4483分，女性：92人\n", "平均成绩：3.2877分，总体：405人\n" ] } ], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "filename = 'data/data_镇海_白班.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": "a7ba7d25-b7a0-4641-a218-b4569d31acb1", "metadata": {}, "source": [ "## 计算测试等级" ] }, { "cell_type": "code", "execution_count": 138, "id": "cff50f06-3221-4340-950f-3a24073b8565", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:10:16.993594Z", "iopub.status.busy": "2024-09-30T08:10:16.992995Z", "iopub.status.idle": "2024-09-30T08:10:17.024014Z", "shell.execute_reply": "2024-09-30T08:10:17.023470Z", "shell.execute_reply.started": "2024-09-30T08:10:16.993539Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0~255分人数：27人,男性：24人,女性:3人\n", "256~332分人数：155人,男性：131人,女性:24人\n", "333~367分人数：146人,男性：104人,女性:42人\n", "368~500分人数：77人,男性：54人,女性:23人\n", "405\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": "16a0d09b-2128-4df4-9745-954f48384244", "metadata": {}, "source": [ "### 计算各年龄段测试等级(女）" ] }, { "cell_type": "code", "execution_count": 139, "id": "6baf0ff2-cdfa-4396-bcf8-3e23a18670dc", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:11:01.790765Z", "iopub.status.busy": "2024-09-30T08:11:01.789996Z", "iopub.status.idle": "2024-09-30T08:11:01.809947Z", "shell.execute_reply": "2024-09-30T08:11:01.809201Z", "shell.execute_reply.started": "2024-09-30T08:11:01.790691Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20-24 {'合格': 1, '良好': 3, '优秀': 0}\n", "25-29 {'良好': 9, '合格': 11, '优秀': 3, '不合格': 0}\n", "30-34 {'合格': 6, '优秀': 5, '良好': 12, '不合格': 2}\n", "35-39 {'良好': 6, '合格': 3, '不合格': 1, '优秀': 5}\n", "40-44 {'良好': 5, '合格': 1, '优秀': 1}\n", "45-49 {'合格': 2, '优秀': 6, '良好': 4, '不合格': 0}\n", "50-54 {'良好': 3, '不合格': 0, '优秀': 2, '合格': 0}\n", "55-80 {'优秀': 1, '合格': 0, '良好': 0, '不合格': 0}\n" ] } ], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "dict2['不合格'] = [0,255]\n", "dict2['合格'] = [256,332]\n", "dict2['良好'] = [333,367]\n", "dict2['优秀'] = [368,500]\n", "dict3 = {}\n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " age = f'{di}-{gao}'\n", " dict3.setdefault(age,{})\n", " i = 0 \n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1): \n", " dict3[age].setdefault(v['level'],0)\n", " if v['sex'] == '女':\n", " dict3[age][v['level']] = dict3[age][v['level']]+1\n", " \n", "for k, v in dict3.items():\n", " print(k,v)" ] }, { "cell_type": "markdown", "id": "79fb3eab-e8d4-42bb-9ba4-8402f3b82b54", "metadata": {}, "source": [ "### 计算各年龄段测试等级(男）" ] }, { "cell_type": "code", "execution_count": 140, "id": "2979cf80-5268-4754-ab8a-11a539315e92", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:11:49.628176Z", "iopub.status.busy": "2024-09-30T08:11:49.627421Z", "iopub.status.idle": "2024-09-30T08:11:49.647219Z", "shell.execute_reply": "2024-09-30T08:11:49.646522Z", "shell.execute_reply.started": "2024-09-30T08:11:49.628086Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20-24 {'合格': 8, '良好': 3, '优秀': 3}\n", "25-29 {'良好': 24, '合格': 33, '优秀': 6, '不合格': 6}\n", "30-34 {'合格': 21, '优秀': 5, '良好': 15, '不合格': 7}\n", "35-39 {'良好': 19, '合格': 28, '不合格': 4, '优秀': 13}\n", "40-44 {'良好': 12, '合格': 8, '优秀': 7}\n", "45-49 {'合格': 10, '优秀': 4, '良好': 7, '不合格': 1}\n", "50-54 {'良好': 16, '不合格': 4, '优秀': 9, '合格': 11}\n", "55-80 {'优秀': 7, '合格': 12, '良好': 8, '不合格': 2}\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": "9a38fc15-579c-42e9-a23c-1050a96e0cf8", "metadata": {}, "source": [ "## 根据年龄汇总人员信息及成绩" ] }, { "cell_type": "code", "execution_count": 141, "id": "8a7cb3b0-d7be-44ac-a1ec-40bdcf29e83b", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:12:43.756100Z", "iopub.status.busy": "2024-09-30T08:12:43.755357Z", "iopub.status.idle": "2024-09-30T08:12:43.770919Z", "shell.execute_reply": "2024-09-30T08:12:43.769768Z", "shell.execute_reply.started": "2024-09-30T08:12:43.756030Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "16~24岁平均成绩：3.24分，人数：18人,男性：14人\n", "25~29岁平均成绩：3.18分，人数：92人,男性：69人\n", "30~34岁平均成绩：3.19分，人数：73人,男性：48人\n", "35~39岁平均成绩：3.33分，人数：79人,男性：64人\n", "40~44岁平均成绩：3.43分，人数：34人,男性：27人\n", "45~49岁平均成绩：3.45分，人数：34人,男性：22人\n", "50~54岁平均成绩：3.38分，人数：45人,男性：40人\n", "55~69岁平均成绩：3.3分，人数：30人,男性：29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": "48debe3b-d0ec-41e8-93ef-921b8e013aa7", "metadata": {}, "source": [ "### 根据年龄汇总人员信息及成绩（男）" ] }, { "cell_type": "code", "execution_count": 142, "id": "c5bb03ca-b7ee-4564-b425-8513e1bff081", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:13:35.726671Z", "iopub.status.busy": "2024-09-30T08:13:35.725976Z", "iopub.status.idle": "2024-09-30T08:13:35.738750Z", "shell.execute_reply": "2024-09-30T08:13:35.737676Z", "shell.execute_reply.started": "2024-09-30T08:13:35.726606Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20~24岁平均成绩：3.21分，人数：14人\n", "25~29岁平均成绩：3.13分，人数：69人\n", "30~34岁平均成绩：3.1分，人数：48人\n", "35~39岁平均成绩：3.3分，人数：64人\n", "40~44岁平均成绩：3.44分，人数：27人\n", "45~49岁平均成绩：3.28分，人数：22人\n", "50~54岁平均成绩：3.34分，人数：40人\n", "55~80岁平均成绩：3.28分，人数：29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": "92bb0683-81ea-4b90-8b74-4a2f43b4835c", "metadata": {}, "source": [ "### 根据年龄汇总人员信息及成绩（女）" ] }, { "cell_type": "code", "execution_count": 143, "id": "bf333998-230c-4365-aadc-b0d1be073b39", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:14:20.172349Z", "iopub.status.busy": "2024-09-30T08:14:20.171955Z", "iopub.status.idle": "2024-09-30T08:14:20.181587Z", "shell.execute_reply": "2024-09-30T08:14:20.180965Z", "shell.execute_reply.started": "2024-09-30T08:14:20.172326Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20~24岁平均成绩：3.37分，人数：4人\n", "25~29岁平均成绩：3.31分，人数：23人\n", "30~34岁平均成绩：3.36分，人数：25人\n", "35~39岁平均成绩：3.48分，人数：15人\n", "40~44岁平均成绩：3.4分，人数：7人\n", "45~49岁平均成绩：3.77分，人数：12人\n", "50~54岁平均成绩：3.71分，人数：5人\n", "55~80岁平均成绩：4.0分，人数：1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": "026d11e4-7f3d-4be5-9fa0-fa3699969c6b", "metadata": {}, "source": [ "## 计算各项目成绩" ] }, { "cell_type": "code", "execution_count": 144, "id": "352c6c29-8929-4210-84c5-8dbc3d5ffeee", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:15:17.750779Z", "iopub.status.busy": "2024-09-30T08:15:17.750013Z", "iopub.status.idle": "2024-09-30T08:15:17.769711Z", "shell.execute_reply": "2024-09-30T08:15:17.768948Z", "shell.execute_reply.started": "2024-09-30T08:15:17.750706Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "BMI 4.07 404\n", "肺活量 3.59 405\n", "握力 3.13 403\n", "坐位体前屈 2.98 400\n", "纵跳 3.48 394\n", "俯卧撑 3.8 308\n", "一分钟仰卧起坐 4.58 78\n", "单脚站立 2.78 397\n", "选择反应时 3.02 388\n", "台阶指数 2.6 381\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": "a13d5644-7cd1-4943-bce9-c6863f75b986", "metadata": {}, "source": [ "## 按照部门计算平均成绩" ] }, { "cell_type": "code", "execution_count": 145, "id": "97f5a1cf-341e-4b99-9549-b6a3fb165849", "metadata": { "execution": { "iopub.execute_input": "2024-09-30T08:16:03.902202Z", "iopub.status.busy": "2024-09-30T08:16:03.901487Z", "iopub.status.idle": "2024-09-30T08:16:03.914044Z", "shell.execute_reply": "2024-09-30T08:16:03.913182Z", "shell.execute_reply.started": "2024-09-30T08:16:03.902118Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "采购中心 3.39 20\n", "公用工程一部 3.28 24\n", "炼油二部 3.21 8\n", "事务中心 3.19 32\n", "公司机关 3.31 83\n", "储运一部 3.29 26\n", "仪表和计量中心 3.31 22\n", "项目管理部 3.36 17\n", "港储部 3.0 7\n", "电气中心 3.18 5\n", "公用工程二部 3.26 13\n", "炼油五部 3.56 16\n", "消防支队 3.14 6\n", "新材料研究院 3.21 11\n", "合成材料部 3.47 9\n", "氢能制造部 3.19 4\n", "油库中心 3.3 17\n", "炼油三部 3.46 8\n", "质管中心 3.2 11\n", "烯烃一部 3.41 21\n", "化学制品部 3.51 5\n", "炼油六部 3.17 6\n", "炼油一部 3.24 10\n", "宣传部 3.11 1\n", "财务部 3.0 1\n", "生产部 3.04 3\n", "发展部 2.78 4\n", "项目部 2.7 2\n", "炼油四部 3.25 4\n", "烯烃二部 3.13 6\n", "炼油七部 2.89 1\n", "储运二部 3.44 2\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": "code", "execution_count": null, "id": "0d043ccc-a241-4b72-912f-7609d3f794a7", "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": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }