{ "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": { "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": "84e0cce3-d2f4-4489-a95e-2a00c3c3fc70", "metadata": {}, "source": [ "### 生成手工成绩sql语言" ] }, { "cell_type": "code", "execution_count": null, "id": "d6498431-2103-4d27-bba9-f1669b710361", "metadata": {}, "outputs": [], "source": [ "import openpyxl\n", "import json\n", "\n", "\n", "wb = openpyxl.load_workbook('data/镇海手工数据.xlsx',data_only=True)\n", "sheet = wb.active\n", "s = ''\n", "list1 = []\n", "for n in range(2, sheet.max_row+1):\n", " ss = ''\n", " list2 = []\n", " list2.append(\"'\"+str(sheet.cell(n, 1).value)+\"'\")\n", " list2.append(\"'\"+str(sheet.cell(n, 2).value)+\"'\")\n", " list2.append(\"'\"+str(sheet.cell(n, 3).value)+\"'\")\n", " list2.append(\"'\"+str(sheet.cell(n, 4).value)+\"'\")\n", " list2.append(\"'\"+str(sheet.cell(n, 5).value)+\"'\")\n", " #list2.append(\"'\"+str(sheet.cell(n, 6).value)+\"'\")\n", " ss = ','.join(list2)\n", " list1.append(\"(\"+ss+\")\")\n", "s = ','.join(list1)\n", "print(s) \n", " " ] }, { "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 = '../item1.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_长炼医院人员2024（湖南青年）.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_长炼医院人员2024（湖南青年）.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_镇海2025-1.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "file_path ='./镇海石化2025/'\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(8,\"0\")\n", " id = str(k)\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": "e81d3d4e-561e-4b43-bceb-b6d9afb38100", "metadata": {}, "source": [ "### 生成报告（按照编号）" ] }, { "cell_type": "code", "execution_count": null, "id": "2e34cf3a-3488-49c2-b18f-48c35b62e6ee", "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2025-1.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "file_path ='./镇海石化2025/'\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n", "i=0\n", "list2 = []\n", "person =['X00309','012947','013304','007231','007243','013612']\n", "for k, v in dict1.items():\n", " list1 = []\n", " mydata = {}\n", " \n", " #id = str(k).rjust(8,\"0\")\n", " id = str(k)\n", " if id in person:\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": "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_胜利采油厂1.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list1 = []\n", "file_path ='./胜利采油厂/'\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'] = '东营胜利采油厂'\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-old2/镇海石化2025'\n", "new_path = 'file/镇海石化2025'\n", "old = []\n", "dict2 = {}\n", "\n", "filename = 'data/result_镇海2025-1.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "fls = glob.glob(f'{fi_path}/*.pdf')\n", "print(len(fls))\n", "for fn in fls:\n", " fi_name =Path(fn).stem.split('-')[0]\n", " code = 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)\n", " print(fn)" ] }, { "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": 10, "id": "02319955-7fb6-4791-ae45-55b03bdadd54", "metadata": { "execution": { "iopub.execute_input": "2025-11-07T06:31:33.947472Z", "iopub.status.busy": "2025-11-07T06:31:33.946853Z", "iopub.status.idle": "2025-11-07T06:31:34.095980Z", "shell.execute_reply": "2025-11-07T06:31:34.095388Z", "shell.execute_reply.started": "2025-11-07T06:31:33.947411Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok\n" ] } ], "source": [ "import os,sys,shutil\n", "import json\n", "import glob\n", "from pathlib import Path\n", "import openpyxl\n", "\n", "fi_path = '/home/songyi/pdf-typescript-old2/镇海石化2025'\n", "\n", "filename = 'data/result_镇海2025-1.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 = 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/2025年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": "34ef7e0d-35ea-4739-a1cb-540c5039afb7", "metadata": {}, "source": [ "## 检查报告错误人员" ] }, { "cell_type": "code", "execution_count": null, "id": "c464fa11-8a0d-44e9-8af0-8c1f50263ceb", "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/北海炼化2024'\n", "\n", "filename = 'data/result_北海炼化2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "print(len(dict1))\n", "fls = glob.glob(f'{fi_path}/*.pdf')\n", "list1 = []\n", "for fn in fls: \n", " fi_name =Path(fn).stem.split('-')[0] \n", " code = int(fi_name)\n", " list1.append(str(code))\n", "for k, v in dict1.items():\n", " if k not in list1:\n", " print(k)" ] }, { "cell_type": "markdown", "id": "732161bb-98f2-4861-ab66-7a374678bcd8", "metadata": { "tags": [], "toc-hr-collapsed": true }, "source": [ "# 体质检测数据管理" ] }, { "cell_type": "markdown", "id": "bb2db5e8-5dc6-4366-a39c-a3600ee5007c", "metadata": {}, "source": [ "## 数据导入Mycrm" ] }, { "cell_type": "markdown", "id": "bc98d772-5841-41a3-ad8f-f7d1ff3b5fde", "metadata": {}, "source": [ "### 导入系统人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "2cd93f45-6613-4a3f-97e4-5236068e1860", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "list1 = []\n", "filename = 'data/person_134.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl) \n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append(line)\n", "#print(list1)\n", "dict1 = {}\n", "for result in list1:\n", " code = str(result[4])\n", " if int(result[1]) == 0:\n", " sex = '男'\n", " else:\n", " sex = '女'\n", " \n", " m_item = str(result[3]) \n", " dict1.setdefault(code,{}) \n", " dict1[code]['name'] = result[0]\n", " dict1[code]['sex'] = sex\n", " dict1[code]['birth'] = result[2]\n", "filename = 'data/天津石化人员清单.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print(len(dict1)) " ] }, { "cell_type": "markdown", "id": "2eb50f19-c15f-4a36-87b7-cd02551d248d", "metadata": {}, "source": [ "### 导入测试项目item" ] }, { "cell_type": "code", "execution_count": null, "id": "0eb37435-9c15-40ef-bd4c-2dffc026f59e", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "data_list = []\n", "for k, v in dict1.items():\n", " data_list.append((int(k),v['name'])) \n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "sql = 'insert into shijiazhuang_item (id,name) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "markdown", "id": "2ba97298-1e7e-4192-8d69-ea59f98e071a", "metadata": {}, "source": [ "### 导入一级部门" ] }, { "cell_type": "code", "execution_count": null, "id": "9f7ed380-95f3-47d4-9eb5-74937af7811f", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "filename = 'data/result_石家庄.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "unit = set()\n", "for k, v in dict1.items():\n", " #if 'sub_unit' not in v.keys():\n", " # print(k,v['name'])\n", " unit.add(v['unit'])\n", "print(unit) \n", "i = 1\n", "dict2 = {}\n", "for item in unit:\n", " dict2[item] = i\n", " i+=1\n", "data_list = []\n", "for k, v in dict2.items():\n", " data_list.append((v,k)) \n", " \n", "sql = 'insert into shijiazhuang_unit (id,name) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "markdown", "id": "b8a1fa7f-08ff-49bb-8052-9f86b1f2ac18", "metadata": {}, "source": [ "### 导入二级部门" ] }, { "cell_type": "code", "execution_count": null, "id": "a13e81f2-467f-42c7-bb46-b547ef7bdd6c", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "filename = 'data/天津石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "unit = set()\n", "for k, v in dict1.items():\n", " #if 'sub_unit' not in v.keys():\n", " # print(k,v['name'])\n", " unit.add(v['unit'])\n", "print(unit) \n", "i = 1\n", "dict2 = {}\n", "for item in unit:\n", " dict2[item] = i\n", " i+=1\n", "data_list = []\n", "dict3 = {}\n", "for k, v in dict1.items():\n", " dict3.setdefault(v['unit'],set())\n", " dict3[v['unit']].add(v['sub_unit'])\n", "i = 1 \n", "for k, v in dict3.items():\n", " unit_id = dict2[k]\n", " for item in v:\n", " data_list.append((i,item,unit_id))\n", " i+=1\n", "sql = 'insert into tianjin_sub_unit (id,name,unit_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "markdown", "id": "12917000-59e0-4f8a-beee-929c6d7b60a0", "metadata": {}, "source": [ "### 生成部门JSON文件" ] }, { "cell_type": "code", "execution_count": null, "id": "5446269c-d324-4a16-b10e-f24d87178d77", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import csv\n", "\n", "dict1 = {}\n", "filename = 'data/shijiazhuang_unit_20230517.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl)\n", " list1 = []\n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append({'id':int(line[0]),'name':line[1]})\n", "dict1['unit'] = list1\n", "\n", "filename = 'data/sub_unit_134.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl)\n", " list1 = []\n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append({'id':int(line[0]),'name':line[1],'unit_id':int(line[2])})\n", "dict1['sub_unit'] = list1\n", "print(dict1)\n", "\n", "filename = 'data/天津石化部门.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print(len(dict1)) " ] }, { "cell_type": "code", "execution_count": null, "id": "5e57329d-a0ef-47b2-9866-fe2a911ff01d", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import csv\n", "\n", "dict1 = {}\n", "filename = 'data/shijiazhuang_unit_20230517.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl)\n", " list1 = []\n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append({'id':int(line[0]),'name':line[1]})\n", " dict1[int(line[0])] = line[1]\n", "\n", "\n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl, ensure_ascii=False) \n", "print(len(dict1)) " ] }, { "cell_type": "markdown", "id": "53bf98fe-0ae9-402f-b8d8-495e8f31df3d", "metadata": {}, "source": [ "### 导入人员信息" ] }, { "cell_type": "code", "execution_count": null, "id": "6af82fd2-b1d6-44b7-8b13-58883b58f8b0", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "filename = 'data/天津石化人员清单.json'\n", "with open(filename,'r') as fl:\n", " person = json.load(fl)\n", " \n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "i = 1\n", "dict2 = {}\n", "for item in unit:\n", " dict2[item] = i\n", " i+=1\n", "data_list = []\n", "dict3 = {}\n", "dict4 = {}\n", "for k, v in dict1.items():\n", " dict3.setdefault(v['unit'],set())\n", " dict3[v['unit']].add(v['sub_unit']) \n", "i = 1 \n", "for k, v in dict3.items():\n", " unit_id = dict2[k]\n", " for item in v:\n", " data_list.append((i,item,unit_id))\n", " i+=1\n", "for item in data_list:\n", " sub_id = item[0]\n", " dict4[sub_id] = {'name':item[1],'unit':item[2]}\n", "dict5 = {}\n", "for k, v in dict1.items():\n", " id_unit = dict2[v['unit']]\n", " sub_name = v['sub_unit']\n", " id_sub = 0\n", " for k1, v1 in dict4.items():\n", " if v1['name'] == sub_name and v1['unit'] == id_unit:\n", " id_sub = int(k1)\n", " if id_sub >0:\n", " dict5[k] = {'unit':id_unit,'sub_unit':id_sub}\n", " else:\n", " print(k,'not fund')\n", "data_list = []\n", "for k, v in dict5.items():\n", " id = int(k)\n", " name = person[k]['name']\n", " sex = person[k]['sex']\n", " birth = person[k]['birth']\n", " phone = ''\n", " note = ''\n", " unit = v['sub_unit']\n", " data_list.append((id,name,sex,birth,unit))\n", "sql = 'insert into tianjin_person (id,name,sex,birth,unit_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!') \n", " " ] }, { "cell_type": "code", "execution_count": null, "id": "c2007c46-38c8-4a20-9917-b0b8743fe2a9", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", " \n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "dict3 = {}\n", "for k,v in dict1.items():\n", " dict3[v] = int(k)\n", "filename = 'data/result_石家庄.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "data_list = []\n", "for k, v in dict2.items():\n", " id = int(k)\n", " name = dict2[k]['name']\n", " sex = dict2[k]['sex']\n", " birth = dict2[k]['birth'] \n", " unit = dict3[dict2[k]['unit']]\n", " data_list.append((id,name,sex,birth,unit))\n", "sql = 'insert into shijiazhuang_person (id,name,sex,birth,unit_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!') " ] }, { "cell_type": "markdown", "id": "fd95a45a-c6df-47c3-9941-2d0579b2c5d9", "metadata": {}, "source": [ "### 导入测试成绩及得分" ] }, { "cell_type": "markdown", "id": "c989de3f-a8ab-47dc-9662-544e4b6a0e2f", "metadata": { "tags": [] }, "source": [ "#### 二级部门导入" ] }, { "cell_type": "code", "execution_count": null, "id": "360e61e9-7895-484b-a9d6-333bdefa1a86", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "for k, v in dict1.items():\n", " dict2[v['name']] = int(k)\n", "\n", "filename = 'data/天津石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "unit = {}\n", "for item in dict1['unit']:\n", " unit[item['name']] = item['id']\n", "\n", "sub_unit = {}\n", "for item in dict1['sub_unit']:\n", " sub_unit.setdefault(item['unit_id'],[])\n", " sub_unit[item['unit_id']].append({'id':item['id'],'name':item['name']})\n", " \n", "filename = 'data/天津石化人员名单.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "person = {}\n", "for k, v in dict1.items():\n", " person[k] = {'unit':v['unit'],'sub_unit':v['sub_unit']}\n", "\n", " \n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "data_list = []\n", "filename = 'data/result_天津.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k, v in dict1.items():\n", " for item in v.keys():\n", " if item in dict2.keys():\n", " item_id = dict2[item]\n", " if v[item]['得分'] == '\\\\N':\n", " score = None\n", " else:\n", " score = int(v[item]['得分'])\n", " unit_name = person[k]['unit'] \n", " sub_unit_name = person[k]['sub_unit']\n", " unit_id = unit[unit_name]\n", " for items in sub_unit[unit_id]:\n", " if items['name'] ==sub_unit_name:\n", " sub_id = items['id'] \n", " data_list.append((v[item]['成绩'],score,int(k),item_id,unit_id,sub_id))\n", " \n", "sql = 'insert into tianjin_records (performance,score,avatar_id_id,item_id_id,unit_id_id,sub_unit_id_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!') \n", " " ] }, { "cell_type": "markdown", "id": "4aeabbbc-5b51-4dd0-b428-83e2012e63c4", "metadata": {}, "source": [ "#### 一级部门导入" ] }, { "cell_type": "code", "execution_count": null, "id": "cb747368-d3ac-4b29-ae4f-ce207d5fcd43", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "for k, v in dict1.items():\n", " dict2[v['name']] = int(k)\n", "\n", "filename = 'data/石家庄石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "dict3 = {}\n", "for k,v in dict1.items():\n", " dict3[v] = int(k)\n", " \n", "\n", "conn = psycopg2.connect(database=\"mycrm\", user=\"postgres\", password=\"songyi\", host=\"localhost\", port=\"5432\")\n", "cursor = conn.cursor()\n", "data_list = []\n", "filename = 'data/result_石家庄.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k, v in dict1.items():\n", " for item in v.keys():\n", " if item in dict2.keys():\n", " item_id = dict2[item] \n", " if v[item]['得分'] == '':\n", " score = None\n", " else:\n", " score = int(v[item]['得分'])\n", " unit_name = v['unit']\n", " unit_id = dict3[unit_name]\n", " data_list.append((v[item]['成绩'],score,int(k),item_id,unit_id))\n", "sql = 'insert into shijiazhuang_records (performance,score,avatar_id_id,item_id_id,unit_id_id) values %s'\n", "ex.execute_values(cursor, sql, data_list, page_size=10000)\n", "#conn.commit()\n", "cursor.close()\n", "conn.close()\n", "print('ok!')" ] }, { "cell_type": "code", "execution_count": null, "id": "51dc35a5-dc07-40a4-9ea7-375ca7f983c3", "metadata": {}, "outputs": [], "source": [ "import json\n", "import psycopg2\n", "from psycopg2 import extras as ex\n", "\n", "filename = '../item.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "for k, v in dict1.items():\n", " dict2[v['name']] = int(k)\n", "\n", "filename = 'data/天津石化部门.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "unit = {}\n", "for item in dict1['unit']:\n", " unit[item['name']] = item['id']\n", "print(unit)" ] }, { "cell_type": "markdown", "id": "5780368e-59c7-4bc1-a130-21b2f7da23de", "metadata": {}, "source": [ "# 体质测试综合报告数据分析" ] }, { "cell_type": "markdown", "id": "0ddf1a23-5963-43ba-9166-c88be749d75d", "metadata": {}, "source": [ "## 清理报告数据" ] }, { "cell_type": "code", "execution_count": null, "id": "46aa847d-e1fe-45bd-85b6-e2d792ec8842", "metadata": {}, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "\n", "filename = 'data/result_胜利采油厂1.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_胜利采油厂.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": null, "id": "63edd636-f034-4aa6-8575-63d5cdb84adb", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "filename = 'data/data_胜利采油厂.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "i = 1\n", "m = 0\n", "f = 0\n", "score = 0\n", "t_score = 0\n", "for k,v in dict1.items():\n", " if v['sex'] == '男':\n", " m = m +1\n", " score = score+v['score']\n", "print(f'平均成绩：{round(score/m,4)}分，男性：{m}人')\n", "t_score = t_score + score\n", "score = 0\n", "for k,v in dict1.items():\n", " if v['sex'] == '女':\n", " f = f +1\n", " score = score+v['score']\n", "print(f'平均成绩：{round(score/f,4)}分，女性：{f}人')\n", "t_score = t_score + score\n", "print(f'平均成绩：{round(t_score/(f+m),4)}分，总体：{(f+m)}人')" ] }, { "cell_type": "markdown", "id": "3277b104-9b53-41c4-9b9a-f9acb71dbce1", "metadata": {}, "source": [ "## 计算测试等级" ] }, { "cell_type": "code", "execution_count": null, "id": "1b4a3f02-9b2e-41fc-ac6c-8163907a07f1", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "\n", "#filename = 'data/data_长炼医院.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "dict2['不合格'] = [0,255]\n", "dict2['合格'] = [256,332]\n", "dict2['良好'] = [333,367]\n", "dict2['优秀'] = [368,500]\n", "\n", "for k1, v1 in dict2.items():\n", " di = v1[0]\n", " gao = v1[1]\n", " i = 0 \n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if int(v['score']*100) in range(di,gao+1):\n", " dict1[k]['level'] = k1\n", " i+=1\n", " if v['sex'] == '男':\n", " m = m +1\n", " else:\n", " f = f+1\n", " print(f'{di}~{gao}分人数：{i}人,男性：{m}人,女性:{f}人')\n", "print(len(dict1))\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) \n", "print('ok')" ] }, { "cell_type": "markdown", "id": "39a1239d-13d8-4583-a163-e6db98c3933b", "metadata": {}, "source": [ "### 计算各年龄段测试等级(女）" ] }, { "cell_type": "code", "execution_count": null, "id": "2d661ca6-6129-4da1-ac25-51d0156babb2", "metadata": { "tags": [] }, "outputs": [], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "dict2['不合格'] = [0,255]\n", "dict2['合格'] = [256,332]\n", "dict2['良好'] = [333,367]\n", "dict2['优秀'] = [368,500]\n", "dict3 = {}\n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " age = f'{di}-{gao}'\n", " dict3.setdefault(age,{})\n", " i = 0 \n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1): \n", " dict3[age].setdefault(v['level'],0)\n", " if v['sex'] == '女':\n", " dict3[age][v['level']] = dict3[age][v['level']]+1\n", " \n", "for k, v in dict3.items():\n", " print(k,v)" ] }, { "cell_type": "markdown", "id": "b7d10bef-405f-49a1-b423-2b972b4d1a44", "metadata": {}, "source": [ "### 计算各年龄段测试等级(男）" ] }, { "cell_type": "code", "execution_count": null, "id": "fc97df37-34ff-4a02-9d26-b5d81b706e46", "metadata": { "tags": [] }, "outputs": [], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "dict2 = {}\n", "dict2['不合格'] = [0,255]\n", "dict2['合格'] = [256,332]\n", "dict2['良好'] = [333,367]\n", "dict2['优秀'] = [368,500]\n", "dict3 = {}\n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " age = f'{di}-{gao}'\n", " dict3.setdefault(age,{})\n", " i = 0 \n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1): \n", " dict3[age].setdefault(v['level'],0)\n", " if v['sex'] == '男':\n", " dict3[age][v['level']] = dict3[age][v['level']]+1\n", " \n", "for k, v in dict3.items():\n", " print(k,v)" ] }, { "cell_type": "markdown", "id": "466355fe-5939-463c-a31e-a3a1beb4e78b", "metadata": {}, "source": [ "## 根据年龄汇总人员信息及成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "dafb86f8-5ee0-4c87-a98f-c7ff0f631fe5", "metadata": { "tags": [] }, "outputs": [], "source": [ "nld = [[16,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " i = 0\n", " score = 0\n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1):\n", " score = score+v['score']\n", " i+=1\n", " if v['sex'] == '男':\n", " m = m +1\n", " if i ==0:\n", " print(f'{di}~{gao}岁平均成绩：0分，人数：0人,男性：{m}人')\n", " else:\n", " print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人,男性：{m}人')" ] }, { "cell_type": "markdown", "id": "dafdffca-6543-4304-af61-4f7cd418ba24", "metadata": {}, "source": [ "### 根据年龄汇总人员信息及成绩（男）" ] }, { "cell_type": "code", "execution_count": null, "id": "347703a1-501b-4800-bd29-16e94f4a6793", "metadata": { "tags": [] }, "outputs": [], "source": [ "import json\n", "\n", "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " i = 0\n", " score = 0\n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1) and v['sex'] == '男':\n", " score = score+v['score']\n", " i+=1\n", " if i ==0:\n", " print(f'{di}~{gao}岁平均成绩：0分，人数：{i}人') \n", " else:\n", " print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人')" ] }, { "cell_type": "markdown", "id": "9b63891e-824a-4772-83f9-0706381ffd14", "metadata": {}, "source": [ "### 根据年龄汇总人员信息及成绩（女）" ] }, { "cell_type": "code", "execution_count": null, "id": "5900d1c7-2f8c-4dfa-a60e-a577fb90f22d", "metadata": { "tags": [] }, "outputs": [], "source": [ "nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n", "\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for item in nld:\n", " di = item[0]\n", " gao = item[1]\n", " i = 0\n", " score = 0\n", " m = 0\n", " f = 0\n", " for k,v in dict1.items():\n", " if v['age'] in range(di,gao+1) and v['sex'] == '女':\n", " score = score+v['score']\n", " i+=1\n", " if i ==0:\n", " print(f'{di}~{gao}岁平均成绩：0分，人数：{i}人') \n", " else:\n", " print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i}人')" ] }, { "cell_type": "markdown", "id": "ca546652-d275-46d3-9b9a-9cb1c3a09a78", "metadata": {}, "source": [ "## 计算各项目成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "ad69c45d-3f62-42df-894d-47424e759029", "metadata": { "tags": [] }, "outputs": [], "source": [ "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "for item in items:\n", " score = 0\n", " n = 0\n", " for k, v in dict1.items(): \n", " if item in v['fits'].keys():\n", " n = n + 1\n", " score =score + int(v['fits'][item]['score'])\n", " print(item,round(score/n,2),n)" ] }, { "cell_type": "markdown", "id": "f005328b-1927-4f62-b530-e7750299c423", "metadata": {}, "source": [ "## 按照部门计算平均成绩" ] }, { "cell_type": "code", "execution_count": null, "id": "dcf152e7-bbcc-47d1-9c5f-83854db35412", "metadata": { "tags": [] }, "outputs": [], "source": [ "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "depart = []\n", "for k, v in dict1.items():\n", " if v['unit'] not in depart:\n", " depart.append(v['unit'])\n", "\n", "for item in depart:\n", " score = 0\n", " n = 0\n", " for k, v in dict1.items():\n", " if item == v['unit']:\n", " score = score + v['score']\n", " n = n +1 \n", " print(item,round(score/n,2),n)" ] }, { "cell_type": "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": null, "id": "d1977ca9-bf12-4f09-ae7b-e8af9eaa82f2", "metadata": {}, "outputs": [], "source": [ "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "depart = []\n", "for k, v in dict1.items():\n", " if v['unit'] not in depart:\n", " depart.append(v['unit'])\n", "\n", "for item in depart:\n", " score = 0\n", " n = 0\n", " for k, v in dict1.items():\n", " if item == v['unit'] 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": null, "id": "d507c7f7-6a91-4695-b700-5e2f77e6dea3", "metadata": {}, "outputs": [], "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": null, "id": "90bc66cd-9f01-410e-9abc-e6f15ada293f", "metadata": {}, "outputs": [], "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_宁夏能化人员.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/北海炼化人员2024.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "dict3 = {}\n", "\n", "for k, v in dict1.items():\n", " unit = v['unit']\n", " dict3.setdefault(unit,{})\n", " for item in items:\n", " dict3[unit].setdefault(item,{})\n", " dict3[unit][item].setdefault('score',0)\n", " dict3[unit][item].setdefault('count',0)\n", " for k1,v1 in v['fits'].items():\n", " if k1 in items:\n", " dict3[unit][k1]['score']+=v1['score']\n", " dict3[unit][k1]['count']+=1\n", "\n", "for k, v in dict3.items():\n", " print(k)\n", " for k1, v1 in v.items():\n", " print(k1,v1['score'],v1['count'])" ] }, { "cell_type": "markdown", "id": "bdb81e20-32ec-4e0e-b2ac-13dac2060068", "metadata": { "tags": [] }, "source": [ "# 问卷数据处理分析" ] }, { "cell_type": "markdown", "id": "1485fc89-4fc2-437d-a29e-b4a0aab12aa0", "metadata": {}, "source": [ "## 常用参数及自定义函数" ] }, { "cell_type": "code", "execution_count": null, "id": "6f9768ce-2ef5-4253-9fc6-49dbdcf00a19", "metadata": {}, "outputs": [], "source": [ "import json\n", "\n", "questions = [\n", " [1],\n", " [-1, 2],\n", " [-1, 2],\n", " [-1, 8],\n", " [-1, 3],\n", " [1],\n", " [-1],\n", " [-1, 7],\n", " [2],\n", " [2],\n", " [2],\n", " [2, 3],\n", " [2],\n", " [2],\n", " [3],\n", " [3],\n", " [3],\n", " [3],\n", " [3],\n", " [4],\n", " [4],\n", " [4],\n", " [4],\n", " [4],\n", " [4],\n", " [4],\n", " [4],\n", " [5],\n", " [5],\n", " [5],\n", " [5],\n", " [5],\n", " [5],\n", " [5],\n", " [5],\n", " [6],\n", " [6],\n", " [6],\n", " [6],\n", " [6],\n", " [6],\n", " [7],\n", " [7],\n", " [7],\n", " [7],\n", " [7],\n", " [7],\n", " [8],\n", " [8],\n", " [8],\n", " [8],\n", " [8],\n", " [8],\n", " [9],\n", " [9],\n", " [9],\n", " [9],\n", " [9],\n", " [9],\n", " [9]\n", "]\n", "\n", "kinds = [\n", " '平和',\n", " '气虚',\n", " '阳虚',\n", " '阴虚',\n", " '痰湿',\n", " '湿热',\n", " '血瘀',\n", " '气郁',\n", " '特禀'\n", "]\n", "\n", "def tcm_calc(arr):\n", " qa = [8, 8, 7, 8, 8, 6, 7, 7, 7]\n", " # 成绩数组\n", " s = [0] * 9\n", " # 遍历五进制\n", " for i in range(len(questions)):\n", " m = arr[i] - 1\n", " for v in questions[i]:\n", " if v < 0:\n", " s[-v - 1] += 4 - m\n", " else:\n", " s[v - 1] += m\n", " return [int((v / qa[i]) * 25) for i, v in enumerate(s)]\n", "\n", "def tcm_kind(score):\n", " kind = 0\n", " near = False\n", " max_kind = 0\n", " max_score = 0\n", " for i in range(1, 9):\n", " if score[i] > max_score:\n", " max_kind = i\n", " max_score = score[i]\n", " if score[0] >= 60 and max_score < 40:\n", " if max_score >= 30:\n", " near = True\n", " kind = max_kind\n", " else:\n", " kind = max_kind\n", " return {\n", " \"kind\": kind,\n", " \"near\": near\n", " }\n", "list2 = ['成就感','愉快心境','放松程度','压力应对','体力充沛','情感充沛度']\n", "list3 = [[5,7],[7,4],[7,4],[7,4],[8,1],[6,1]] \n", "list4 = ['颈椎','胸椎','腰椎','骶尾椎']\n", "list5 = [[0,10,10],[10,17,7],[17,24,6],[24,26,2]]\n", "\n", "\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", " ]" ] }, { "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_南京化工-3.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(v['name'])\n", " list3.append(v['sex'])\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/南京化工中医情况明细表（202510）.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_北海炼化2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "list4 = []\n", "for k, v in dict1.items():\n", " if 'psy' in v.keys():\n", " list5 = []\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", " list5.append(k)\n", " for i in range(0,6):\n", " score = int(dict3[i+1]/list3[i][0]/list3[i][1]*100)\n", " list5.append(score)\n", " list4.append(list5)\n", "filename = 'data/北海炼化心理情况明细表2024.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "\n", "for row in list4:\n", " sheet.append(row)\n", " \n", "wb.save(filename)\n", "print('ok') " ] }, { "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_新疆油田采油工艺研究院-1.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list6 = []\n", "for k, v in dict1.items():\n", " if 'spine' in v.keys():\n", " list7 = []\n", " spine = v['spine']\n", " list7.append(k)\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)\n", " list7.append(int(score/list5[i][2]*100)-100)\n", " list6.append(list7)\n", "filename = 'data/新疆油田采油工艺研究院脊柱情况明细表.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "\n", "for row in list6:\n", " sheet.append(row)\n", " \n", "wb.save(filename)\n", "print('ok') " ] }, { "cell_type": "markdown", "id": "b9d5bad6-4d72-43d7-b86b-55c9b9d33af2", "metadata": {}, "source": [ "## 导出脊柱明细表" ] }, { "cell_type": "code", "execution_count": null, "id": "1a5a10cb-f6bc-4e3a-83cc-78b9c0cbe994", "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_北海炼化2024.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "list6 = []\n", "for k, v in dict1.items():\n", " if 'spine' in v.keys():\n", " list7 = []\n", " spine = v['spine']\n", " list7.append(k)\n", " list7.append(v['name'])\n", " list7.append(v['sex'])\n", " list7.append(v['age'])\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)\n", " list7.append(int(score/list5[i][2]*100)-100)\n", " for item in v['spine']:\n", " list7.append(item)\n", " list6.append(list7)\n", "filename = 'data/北海炼化脊柱情况明细表2024.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "\n", "for row in list6:\n", " sheet.append(row)\n", " \n", "wb.save(filename)\n", "print('ok') " ] }, { "cell_type": "markdown", "id": "5fcd0a68-b6c7-4456-9ae7-7bbc4daecc99", "metadata": {}, "source": [ "## 导出体质监测情况表" ] }, { "cell_type": "code", "execution_count": null, "id": "9ecd3ad8-c8af-4f3e-90e5-1618fea905a4", "metadata": {}, "outputs": [], "source": [ "import openpyxl\n", "\n", "list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n", "filename = 'data/result_南京化工-3.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "data_list = []\n", "for k, v in dict1.items():\n", " list6 = []\n", " list6.append(str(k).rjust(4,'0'))\n", " list6.append(v['name'])\n", " list6.append(v['sex'])\n", " #list6.append(v['unit'])\n", " list6.append(v['age'])\n", " if 'bmi' in v.keys():\n", " bmi = v['bmi']['成绩']\n", " list6.append(bmi.split(',')[0]+' 厘米')\n", " list6.append(bmi.split(',')[1]+' 千克')\n", " list6.append(v['bmi']['score'])\n", " else:\n", " list6.append('')\n", " list6.append('')\n", " list6.append('')\n", " for xm in list_item:\n", " if xm in v.keys():\n", " list6.append(v[xm]['成绩'])\n", " list6.append(v[xm]['score'])\n", " else:\n", " list6.append('')\n", " list6.append('')\n", " \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(k,kinds[kind], near, score)\n", " list6.append(kinds[kind])\n", " if near:\n", " list6.append('是')\n", " else:\n", " list6.append('')\n", " for item in score:\n", " list6.append(item)\n", " else:\n", " for i in range(0,11):\n", " list6.append('')\n", " i+=1\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", " \n", " for i in range(0,6):\n", " score = int(dict3[i+1]/list3[i][0]/list3[i][1]*100)\n", " list6.append(score)\n", " else:\n", " for i in range(0,6):\n", " list6.append('')\n", " i+=1\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", " list6.append(int(score/list5[i][2]*100)-100)\n", " else:\n", " for i in range(0,4):\n", " list6.append('')\n", " i+=1\n", " data_list.append(list6)\n", "filename = 'data/南京化工中医情况明细表（202510）.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "#sheet.append(title)\n", "for row in data_list:\n", " sheet.append(row)\n", " \n", "wb.save(filename) " ] }, { "cell_type": "code", "execution_count": null, "id": "200d10a8-15a7-4ec9-b407-ffb06c0e19be", "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 }