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jupyter/体测单位/体质检测数据处理.ipynb
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{
"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_沧州炼化-1.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"list1 = []\n",
"file_path ='./沧州炼化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).rjust(4,\"0\")\n",
" mydata['path'] = file_path+id+'-'+ v['name']+'.pdf'\n",
" mydata['title'] = '中国石化沧州炼化公司'\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/沧州炼化2025'\n",
"new_path = 'file/沧州炼化2025'\n",
"old = []\n",
"dict2 = {}\n",
"\n",
"filename = 'data/result_沧州炼化-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 = str(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)\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": null,
"id": "02319955-7fb6-4791-ae45-55b03bdadd54",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"import os,sys,shutil\n",
"import json\n",
"import glob\n",
"from pathlib import Path\n",
"import openpyxl\n",
"\n",
"fi_path = '/home/songyi/pdf-typescript-old2/沧州炼化2025'\n",
"\n",
"filename = 'data/result_沧州炼化-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 = str(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/2025年沧州炼化体测报告明细表.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": 151,
"id": "46aa847d-e1fe-45bd-85b6-e2d792ec8842",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:44:17.370454Z",
"iopub.status.busy": "2025-11-24T14:44:17.369923Z",
"iopub.status.idle": "2025-11-24T14:44:17.446158Z",
"shell.execute_reply": "2025-11-24T14:44:17.445652Z",
"shell.execute_reply.started": "2025-11-24T14:44:17.370404Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1221\n"
]
}
],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"\n",
"filename = 'data/result_沧州炼化-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",
" 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_沧州炼化.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": 154,
"id": "63edd636-f034-4aa6-8575-63d5cdb84adb",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:02.470995Z",
"iopub.status.busy": "2025-11-24T14:48:02.470445Z",
"iopub.status.idle": "2025-11-24T14:48:02.669216Z",
"shell.execute_reply": "2025-11-24T14:48:02.668674Z",
"shell.execute_reply.started": "2025-11-24T14:48:02.470943Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"平均成绩:2.7312分,男性:997人\n",
"平均成绩:3.2382分,女性:224人\n",
"平均成绩:2.8242分,总体:1221人\n"
]
}
],
"source": [
"import json\n",
"\n",
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"filename = 'data/data_沧州炼化.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": 155,
"id": "1b4a3f02-9b2e-41fc-ac6c-8163907a07f1",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:04.750451Z",
"iopub.status.busy": "2025-11-24T14:48:04.749903Z",
"iopub.status.idle": "2025-11-24T14:48:04.814681Z",
"shell.execute_reply": "2025-11-24T14:48:04.814131Z",
"shell.execute_reply.started": "2025-11-24T14:48:04.750403Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0~255分人数:383人,男性:358人,女性:25人\n",
"256~332分人数:551人,男性:458人,女性:93人\n",
"333~367分人数:195人,男性:130人,女性:65人\n",
"368~500分人数:92人,男性:51人,女性:41人\n",
"1221\n",
"ok\n"
]
}
],
"source": [
"import json\n",
"\n",
"items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"\n",
"#filename = 'data/data_长炼医院.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"dict2 = {}\n",
"dict2['不合格'] = [0,255]\n",
"dict2['合格'] = [256,332]\n",
"dict2['良好'] = [333,367]\n",
"dict2['优秀'] = [368,500]\n",
"\n",
"for k1, v1 in dict2.items():\n",
" di = v1[0]\n",
" gao = v1[1]\n",
" i = 0 \n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if int(v['score']*100) in range(di,gao+1):\n",
" dict1[k]['level'] = k1\n",
" i+=1\n",
" if v['sex'] == '男':\n",
" m = m +1\n",
" else:\n",
" f = f+1\n",
" print(f'{di}~{gao}分人数:{i}人,男性:{m}人,女性:{f}人')\n",
"print(len(dict1))\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict1, fl) \n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "39a1239d-13d8-4583-a163-e6db98c3933b",
"metadata": {},
"source": [
"### 计算各年龄段测试等级(女)"
]
},
{
"cell_type": "code",
"execution_count": 156,
"id": "2d661ca6-6129-4da1-ac25-51d0156babb2",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:07.278548Z",
"iopub.status.busy": "2025-11-24T14:48:07.277877Z",
"iopub.status.idle": "2025-11-24T14:48:07.309085Z",
"shell.execute_reply": "2025-11-24T14:48:07.308611Z",
"shell.execute_reply.started": "2025-11-24T14:48:07.278486Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20-24 {'合格': 2, '不合格': 1, '良好': 1, '优秀': 0}\n",
"25-29 {'合格': 9, '不合格': 3, '良好': 7, '优秀': 2}\n",
"30-34 {'合格': 5, '不合格': 0, '优秀': 3, '良好': 2}\n",
"35-39 {'合格': 5, '不合格': 4, '良好': 4, '优秀': 5}\n",
"40-44 {'合格': 10, '不合格': 5, '优秀': 5, '良好': 11}\n",
"45-49 {'不合格': 12, '良好': 29, '合格': 48, '优秀': 15}\n",
"50-54 {'合格': 14, '不合格': 0, '优秀': 10, '良好': 11}\n",
"55-80 {'合格': 0, '不合格': 0, '良好': 0, '优秀': 1}\n"
]
}
],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"dict2 = {}\n",
"dict2['不合格'] = [0,255]\n",
"dict2['合格'] = [256,332]\n",
"dict2['良好'] = [333,367]\n",
"dict2['优秀'] = [368,500]\n",
"dict3 = {}\n",
"for item in nld:\n",
" di = item[0]\n",
" gao = item[1]\n",
" age = f'{di}-{gao}'\n",
" dict3.setdefault(age,{})\n",
" i = 0 \n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if v['age'] in range(di,gao+1): \n",
" dict3[age].setdefault(v['level'],0)\n",
" if v['sex'] == '女':\n",
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
" \n",
"for k, v in dict3.items():\n",
" print(k,v)"
]
},
{
"cell_type": "markdown",
"id": "b7d10bef-405f-49a1-b423-2b972b4d1a44",
"metadata": {},
"source": [
"### 计算各年龄段测试等级(男)"
]
},
{
"cell_type": "code",
"execution_count": 157,
"id": "fc97df37-34ff-4a02-9d26-b5d81b706e46",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:10.182242Z",
"iopub.status.busy": "2025-11-24T14:48:10.181626Z",
"iopub.status.idle": "2025-11-24T14:48:10.208838Z",
"shell.execute_reply": "2025-11-24T14:48:10.208242Z",
"shell.execute_reply.started": "2025-11-24T14:48:10.182182Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20-24 {'合格': 15, '不合格': 9, '良好': 3, '优秀': 2}\n",
"25-29 {'合格': 31, '不合格': 22, '良好': 3, '优秀': 1}\n",
"30-34 {'合格': 22, '不合格': 8, '优秀': 0, '良好': 4}\n",
"35-39 {'合格': 65, '不合格': 27, '良好': 21, '优秀': 6}\n",
"40-44 {'合格': 56, '不合格': 50, '优秀': 5, '良好': 16}\n",
"45-49 {'不合格': 49, '良好': 23, '合格': 68, '优秀': 6}\n",
"50-54 {'合格': 118, '不合格': 99, '优秀': 21, '良好': 31}\n",
"55-80 {'合格': 83, '不合格': 94, '良好': 29, '优秀': 10}\n"
]
}
],
"source": [
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"dict2 = {}\n",
"dict2['不合格'] = [0,255]\n",
"dict2['合格'] = [256,332]\n",
"dict2['良好'] = [333,367]\n",
"dict2['优秀'] = [368,500]\n",
"dict3 = {}\n",
"for item in nld:\n",
" di = item[0]\n",
" gao = item[1]\n",
" age = f'{di}-{gao}'\n",
" dict3.setdefault(age,{})\n",
" i = 0 \n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if v['age'] in range(di,gao+1): \n",
" dict3[age].setdefault(v['level'],0)\n",
" if v['sex'] == '男':\n",
" dict3[age][v['level']] = dict3[age][v['level']]+1\n",
" \n",
"for k, v in dict3.items():\n",
" print(k,v)"
]
},
{
"cell_type": "markdown",
"id": "466355fe-5939-463c-a31e-a3a1beb4e78b",
"metadata": {},
"source": [
"## 根据年龄汇总人员信息及成绩"
]
},
{
"cell_type": "code",
"execution_count": 158,
"id": "dafb86f8-5ee0-4c87-a98f-c7ff0f631fe5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:12.941585Z",
"iopub.status.busy": "2025-11-24T14:48:12.941037Z",
"iopub.status.idle": "2025-11-24T14:48:12.968568Z",
"shell.execute_reply": "2025-11-24T14:48:12.967973Z",
"shell.execute_reply.started": "2025-11-24T14:48:12.941536Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"16~24岁平均成绩:2.79分,人数:33人,男性:29人\n",
"25~29岁平均成绩:2.78分,人数:78人,男性:57人\n",
"30~34岁平均成绩:2.86分,人数:44人,男性:34人\n",
"35~39岁平均成绩:2.92分,人数:137人,男性:119人\n",
"40~44岁平均成绩:2.8分,人数:158人,男性:127人\n",
"45~49岁平均成绩:2.93分,人数:250人,男性:146人\n",
"50~54岁平均成绩:2.83分,人数:304人,男性:269人\n",
"55~69岁平均成绩:2.67分,人数:217人,男性:216人\n"
]
}
],
"source": [
"nld = [[16,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,69]]\n",
"\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"for item in nld:\n",
" di = item[0]\n",
" gao = item[1]\n",
" i = 0\n",
" score = 0\n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if v['age'] in range(di,gao+1):\n",
" score = score+v['score']\n",
" i+=1\n",
" if v['sex'] == '男':\n",
" m = m +1\n",
" if i ==0:\n",
" print(f'{di}~{gao}岁平均成绩:0分,人数:0人,男性:{m}人')\n",
" else:\n",
" print(f'{di}~{gao}岁平均成绩:{round(score/i,2)}分,人数:{i}人,男性:{m}人')"
]
},
{
"cell_type": "markdown",
"id": "dafdffca-6543-4304-af61-4f7cd418ba24",
"metadata": {},
"source": [
"### 根据年龄汇总人员信息及成绩(男)"
]
},
{
"cell_type": "code",
"execution_count": 159,
"id": "347703a1-501b-4800-bd29-16e94f4a6793",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:15.372851Z",
"iopub.status.busy": "2025-11-24T14:48:15.372157Z",
"iopub.status.idle": "2025-11-24T14:48:15.394637Z",
"shell.execute_reply": "2025-11-24T14:48:15.394035Z",
"shell.execute_reply.started": "2025-11-24T14:48:15.372789Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20~24岁平均成绩:2.77分,人数:29人\n",
"25~29岁平均成绩:2.63分,人数:57人\n",
"30~34岁平均成绩:2.69分,人数:34人\n",
"35~39岁平均成绩:2.86分,人数:119人\n",
"40~44岁平均成绩:2.7分,人数:127人\n",
"45~49岁平均成绩:2.75分,人数:146人\n",
"50~54岁平均成绩:2.75分,人数:269人\n",
"55~80岁平均成绩:2.66分,人数:216人\n"
]
}
],
"source": [
"import json\n",
"\n",
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
"\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"for item in nld:\n",
" di = item[0]\n",
" gao = item[1]\n",
" i = 0\n",
" score = 0\n",
" m = 0\n",
" f = 0\n",
" for k,v in dict1.items():\n",
" if v['age'] in range(di,gao+1) and v['sex'] == '男':\n",
" score = score+v['score']\n",
" i+=1\n",
" if i ==0:\n",
" print(f'{di}~{gao}岁平均成绩:0分,人数:{i}人') \n",
" else:\n",
" print(f'{di}~{gao}岁平均成绩:{round(score/i,2)}分,人数:{i}人')"
]
},
{
"cell_type": "markdown",
"id": "9b63891e-824a-4772-83f9-0706381ffd14",
"metadata": {},
"source": [
"### 根据年龄汇总人员信息及成绩(女)"
]
},
{
"cell_type": "code",
"execution_count": 160,
"id": "5900d1c7-2f8c-4dfa-a60e-a577fb90f22d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:17.652548Z",
"iopub.status.busy": "2025-11-24T14:48:17.651903Z",
"iopub.status.idle": "2025-11-24T14:48:17.677973Z",
"shell.execute_reply": "2025-11-24T14:48:17.677393Z",
"shell.execute_reply.started": "2025-11-24T14:48:17.652491Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"20~24岁平均成绩:2.94分,人数:4人\n",
"25~29岁平均成绩:3.19分,人数:21人\n",
"30~34岁平均成绩:3.44分,人数:10人\n",
"35~39岁平均成绩:3.28分,人数:18人\n",
"40~44岁平均成绩:3.18分,人数:31人\n",
"45~49岁平均成绩:3.18分,人数:104人\n",
"50~54岁平均成绩:3.44分,人数:35人\n",
"55~80岁平均成绩:4.12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": "ca546652-d275-46d3-9b9a-9cb1c3a09a78",
"metadata": {},
"source": [
"## 计算各项目成绩"
]
},
{
"cell_type": "code",
"execution_count": 161,
"id": "ad69c45d-3f62-42df-894d-47424e759029",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:20.700694Z",
"iopub.status.busy": "2025-11-24T14:48:20.699169Z",
"iopub.status.idle": "2025-11-24T14:48:20.724432Z",
"shell.execute_reply": "2025-11-24T14:48:20.723863Z",
"shell.execute_reply.started": "2025-11-24T14:48:20.700633Z"
},
"scrolled": true,
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"BMI 3.04 1212\n",
"肺活量 3.23 1202\n",
"握力 2.56 1211\n",
"坐位体前屈 3.26 1144\n",
"纵跳 2.17 1152\n",
"俯卧撑 2.5 955\n",
"一分钟仰卧起坐 3.8 202\n",
"单脚站立 2.58 1184\n",
"选择反应时 3.26 1204\n",
"台阶指数 2.72 768\n"
]
}
],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"for item in items:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items(): \n",
" if item in v['fits'].keys():\n",
" n = n + 1\n",
" score =score + int(v['fits'][item]['score'])\n",
" print(item,round(score/n,2),n)"
]
},
{
"cell_type": "markdown",
"id": "f005328b-1927-4f62-b530-e7750299c423",
"metadata": {},
"source": [
"## 按照部门计算平均成绩"
]
},
{
"cell_type": "code",
"execution_count": 152,
"id": "dcf152e7-bbcc-47d1-9c5f-83854db35412",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:44:34.448484Z",
"iopub.status.busy": "2025-11-24T14:44:34.447872Z",
"iopub.status.idle": "2025-11-24T14:44:34.473938Z",
"shell.execute_reply": "2025-11-24T14:44:34.473308Z",
"shell.execute_reply.started": "2025-11-24T14:44:34.448431Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"应急救援中心 2.9 82\n",
"质量计量中心 2.94 125\n",
"公用工程部 2.77 164\n",
"财务资产部 3.1 15\n",
"炼油一部 2.74 163\n",
"炼油二部 2.8 145\n",
"炼油三部 2.88 144\n",
"储运部 2.68 139\n",
"行政事务中心 2.65 90\n",
"总经理办公室 3.1 9\n",
"安全环保部 3.03 14\n",
"计划经营部 2.96 12\n",
"党群工作部 3.31 14\n",
"物资采购中心 3.02 24\n",
"生产技术部 2.95 19\n",
"设备工程部 2.99 22\n",
"监督审计部 2.88 10\n",
"党委组织部 2.95 10\n",
"发展规划部 3.15 7\n",
"企管法律部 2.98 13\n"
]
}
],
"source": [
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"depart = []\n",
"for k, v in dict1.items():\n",
" if v['unit'] not in depart:\n",
" depart.append(v['unit'])\n",
"\n",
"for item in depart:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items():\n",
" if item == v['unit']:\n",
" score = score + v['score']\n",
" n = n +1 \n",
" print(item,round(score/n,2),n)"
]
},
{
"cell_type": "markdown",
"id": "83ca1488-9b2d-493c-b540-904a5f0af114",
"metadata": {},
"source": [
"## 按照部门计算平均成绩(女性)"
]
},
{
"cell_type": "code",
"execution_count": 167,
"id": "d1977ca9-bf12-4f09-ae7b-e8af9eaa82f2",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:53:54.924386Z",
"iopub.status.busy": "2025-11-24T14:53:54.923677Z",
"iopub.status.idle": "2025-11-24T14:53:54.952891Z",
"shell.execute_reply": "2025-11-24T14:53:54.952311Z",
"shell.execute_reply.started": "2025-11-24T14:53:54.924307Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"应急救援中心 2.9 82\n",
"质量计量中心 2.94 125\n",
"公用工程部 2.77 164\n",
"财务资产部 3.1 15\n",
"炼油一部 2.74 163\n",
"炼油二部 2.8 145\n",
"炼油三部 2.88 144\n",
"储运部 2.68 139\n",
"行政事务中心 2.65 90\n",
"总经理办公室 3.1 9\n",
"安全环保部 3.03 14\n",
"计划经营部 2.96 12\n",
"党群工作部 3.31 14\n",
"物资采购中心 3.02 24\n",
"生产技术部 2.95 19\n",
"设备工程部 2.99 22\n",
"监督审计部 2.88 10\n",
"党委组织部 2.95 10\n",
"发展规划部 3.15 7\n",
"企管法律部 2.98 13\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",
" 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": 163,
"id": "d507c7f7-6a91-4695-b700-5e2f77e6dea3",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:48:33.771404Z",
"iopub.status.busy": "2025-11-24T14:48:33.770838Z",
"iopub.status.idle": "2025-11-24T14:48:33.790371Z",
"shell.execute_reply": "2025-11-24T14:48:33.789671Z",
"shell.execute_reply.started": "2025-11-24T14:48:33.771338Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"应急救援中心 5 18 39 20\n",
"质量计量中心 13 21 63 28\n",
"公用工程部 10 25 69 60\n",
"财务资产部 3 3 7 2\n",
"炼油一部 5 17 85 56\n",
"炼油二部 10 25 61 49\n",
"炼油三部 16 25 59 44\n",
"储运部 11 12 57 59\n",
"行政事务中心 4 9 41 36\n",
"总经理办公室 0 4 3 2\n",
"安全环保部 3 2 6 3\n",
"计划经营部 2 2 5 3\n",
"党群工作部 2 6 6 0\n",
"物资采购中心 4 4 12 4\n",
"生产技术部 1 3 12 3\n",
"设备工程部 0 8 8 6\n",
"监督审计部 0 3 5 2\n",
"党委组织部 0 3 5 2\n",
"发展规划部 2 1 3 1\n",
"企管法律部 1 4 5 3\n"
]
}
],
"source": [
"import json\n",
"\n",
"items = ['优秀','良好','合格','不合格'] \n",
"\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"\n",
"dict3 = {}\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" dict3.setdefault(unit,{})\n",
" for item in items:\n",
" dict3[unit].setdefault(item,0)\n",
"\n",
"for k, v in dict1.items():\n",
" unit = v['unit']\n",
" #dict3.setdefault(unit,{})\n",
" #for item in items:\n",
" #dict3[unit].setdefault(v['level'],0)\n",
" dict3[unit][v['level']] +=1\n",
"for k, v in dict3.items():\n",
" print(k,v['优秀'],v['良好'],v['合格'],v['不合格'])"
]
},
{
"cell_type": "markdown",
"id": "6345e3dc-509c-4a6f-8a0a-5c972d6f5828",
"metadata": {},
"source": [
"## 计算部门成绩"
]
},
{
"cell_type": "code",
"execution_count": 168,
"id": "90bc66cd-9f01-410e-9abc-e6f15ada293f",
"metadata": {
"execution": {
"iopub.execute_input": "2025-11-24T14:55:54.386010Z",
"iopub.status.busy": "2025-11-24T14:55:54.385455Z",
"iopub.status.idle": "2025-11-24T14:55:54.420009Z",
"shell.execute_reply": "2025-11-24T14:55:54.419528Z",
"shell.execute_reply.started": "2025-11-24T14:55:54.385957Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"应急救援中心\n",
"BMI 228 82\n",
"肺活量 240 82\n",
"握力 212 82\n",
"坐位体前屈 246 78\n",
"纵跳 189 77\n",
"俯卧撑 280 76\n",
"一分钟仰卧起坐 7 2\n",
"单脚站立 179 77\n",
"选择反应时 275 82\n",
"台阶指数 159 53\n",
"质量计量中心\n",
"BMI 427 123\n",
"肺活量 426 125\n",
"握力 302 124\n",
"坐位体前屈 371 115\n",
"纵跳 251 116\n",
"俯卧撑 135 62\n",
"一分钟仰卧起坐 195 51\n",
"单脚站立 330 120\n",
"选择反应时 410 123\n",
"台阶指数 207 74\n",
"公用工程部\n",
"BMI 505 163\n",
"肺活量 520 160\n",
"握力 406 161\n",
"坐位体前屈 467 149\n",
"纵跳 335 158\n",
"俯卧撑 327 137\n",
"一分钟仰卧起坐 61 15\n",
"单脚站立 370 158\n",
"选择反应时 511 160\n",
"台阶指数 280 98\n",
"财务资产部\n",
"BMI 57 15\n",
"肺活量 48 15\n",
"握力 27 15\n",
"坐位体前屈 55 13\n",
"纵跳 33 14\n",
"俯卧撑 19 5\n",
"一分钟仰卧起坐 37 9\n",
"单脚站立 43 14\n",
"选择反应时 52 15\n",
"台阶指数 24 10\n",
"炼油一部\n",
"BMI 491 161\n",
"肺活量 505 163\n",
"握力 430 163\n",
"坐位体前屈 492 157\n",
"纵跳 315 154\n",
"俯卧撑 307 139\n",
"一分钟仰卧起坐 67 19\n",
"单脚站立 406 160\n",
"选择反应时 523 161\n",
"台阶指数 271 102\n",
"炼油二部\n",
"BMI 402 144\n",
"肺活量 463 144\n",
"握力 380 144\n",
"坐位体前屈 466 139\n",
"纵跳 321 142\n",
"俯卧撑 233 112\n",
"一分钟仰卧起坐 110 29\n",
"单脚站立 368 143\n",
"选择反应时 462 143\n",
"台阶指数 288 98\n",
"炼油三部\n",
"BMI 462 142\n",
"肺活量 463 138\n",
"握力 364 144\n",
"坐位体前屈 471 131\n",
"纵跳 247 131\n",
"俯卧撑 335 124\n",
"一分钟仰卧起坐 61 15\n",
"单脚站立 348 141\n",
"选择反应时 476 143\n",
"台阶指数 230 84\n",
"储运部\n",
"BMI 392 138\n",
"肺活量 416 137\n",
"握力 360 136\n",
"坐位体前屈 428 133\n",
"纵跳 256 131\n",
"俯卧撑 283 126\n",
"一分钟仰卧起坐 28 9\n",
"单脚站立 334 136\n",
"选择反应时 415 138\n",
"台阶指数 213 74\n",
"行政事务中心\n",
"BMI 248 90\n",
"肺活量 263 85\n",
"握力 222 88\n",
"坐位体前屈 259 80\n",
"纵跳 143 82\n",
"俯卧撑 171 72\n",
"一分钟仰卧起坐 26 9\n",
"单脚站立 200 83\n",
"选择反应时 278 86\n",
"台阶指数 115 44\n",
"总经理办公室\n",
"BMI 25 9\n",
"肺活量 31 9\n",
"握力 24 9\n",
"坐位体前屈 24 8\n",
"纵跳 24 8\n",
"俯卧撑 9 3\n",
"一分钟仰卧起坐 20 5\n",
"单脚站立 34 9\n",
"选择反应时 28 9\n",
"台阶指数 21 8\n",
"安全环保部\n",
"BMI 38 14\n",
"肺活量 48 14\n",
"握力 40 14\n",
"坐位体前屈 40 13\n",
"纵跳 36 13\n",
"俯卧撑 24 10\n",
"一分钟仰卧起坐 11 3\n",
"单脚站立 45 13\n",
"选择反应时 50 13\n",
"台阶指数 36 13\n",
"计划经营部\n",
"BMI 38 12\n",
"肺活量 39 11\n",
"握力 32 12\n",
"坐位体前屈 32 11\n",
"纵跳 30 11\n",
"俯卧撑 15 6\n",
"一分钟仰卧起坐 20 5\n",
"单脚站立 30 12\n",
"选择反应时 45 12\n",
"台阶指数 23 11\n",
"党群工作部\n",
"BMI 58 14\n",
"肺活量 51 14\n",
"握力 36 14\n",
"坐位体前屈 45 14\n",
"纵跳 41 14\n",
"俯卧撑 19 6\n",
"一分钟仰卧起坐 32 7\n",
"单脚站立 51 14\n",
"选择反应时 50 14\n",
"台阶指数 27 13\n",
"物资采购中心\n",
"BMI 72 24\n",
"肺活量 89 24\n",
"握力 65 24\n",
"坐位体前屈 88 24\n",
"纵跳 56 23\n",
"俯卧撑 45 15\n",
"一分钟仰卧起坐 33 8\n",
"单脚站立 61 24\n",
"选择反应时 76 24\n",
"台阶指数 41 16\n",
"生产技术部\n",
"BMI 57 19\n",
"肺活量 67 19\n",
"握力 47 19\n",
"坐位体前屈 56 18\n",
"纵跳 42 17\n",
"俯卧撑 45 17\n",
"一分钟仰卧起坐 3 1\n",
"单脚站立 61 19\n",
"选择反应时 68 19\n",
"台阶指数 32 14\n",
"设备工程部\n",
"BMI 74 22\n",
"肺活量 71 22\n",
"握力 53 22\n",
"坐位体前屈 71 22\n",
"纵跳 67 22\n",
"俯卧撑 62 17\n",
"一分钟仰卧起坐 18 5\n",
"单脚站立 60 22\n",
"选择反应时 68 22\n",
"台阶指数 49 22\n",
"监督审计部\n",
"BMI 28 10\n",
"肺活量 32 10\n",
"握力 19 10\n",
"坐位体前屈 28 10\n",
"纵跳 27 10\n",
"俯卧撑 22 7\n",
"一分钟仰卧起坐 12 3\n",
"单脚站立 35 10\n",
"选择反应时 31 10\n",
"台阶指数 22 9\n",
"党委组织部\n",
"BMI 26 10\n",
"肺活量 37 10\n",
"握力 25 10\n",
"坐位体前屈 29 10\n",
"纵跳 30 10\n",
"俯卧撑 14 6\n",
"一分钟仰卧起坐 12 4\n",
"单脚站立 34 10\n",
"选择反应时 37 10\n",
"台阶指数 22 10\n",
"发展规划部\n",
"BMI 19 7\n",
"肺活量 28 7\n",
"握力 18 7\n",
"坐位体前屈 23 7\n",
"纵跳 22 6\n",
"俯卧撑 20 6\n",
"一分钟仰卧起坐 5 1\n",
"单脚站立 19 6\n",
"选择反应时 28 7\n",
"台阶指数 11 6\n",
"企管法律部\n",
"BMI 37 13\n",
"肺活量 45 13\n",
"握力 36 13\n",
"坐位体前屈 37 12\n",
"纵跳 32 13\n",
"俯卧撑 25 9\n",
"一分钟仰卧起坐 9 2\n",
"单脚站立 42 13\n",
"选择反应时 44 13\n",
"台阶指数 21 9\n"
]
}
],
"source": [
"import json\n",
"\n",
"items = ['BMI','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数'] \n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"\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": "422a3a6e-468d-4092-9da0-3692814374ca",
"metadata": {},
"source": [
"## 统计班次成绩"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0cec9f15-91dd-49e5-9efd-96b6bac0a86f",
"metadata": {},
"outputs": [],
"source": [
"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_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"banci = []\n",
"for k, v in dict1.items():\n",
" if v['banci'] not in banci:\n",
" banci.append(v['banci'])\n",
"\n",
"for item in banci:\n",
" score = 0\n",
" n = 0\n",
" for k, v in dict1.items():\n",
" if item == v['banci'] and v['sex'] == '女':\n",
" score = score + v['score']\n",
" n = n +1 \n",
" print(item,round(score/n,2),n)"
]
},
{
"cell_type": "markdown",
"id": "d0266733-3d7a-4903-952b-6ed9a6b45961",
"metadata": {},
"source": [
"## 统计班次测试等级"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "127016d1-9aba-45bb-8205-4f4f424eb02e",
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"items = ['优秀','良好','合格','不合格'] \n",
"\n",
"dict3 = {}\n",
"for k, v in dict1.items():\n",
" banci = v['banci']\n",
" dict3.setdefault(banci,{})\n",
" for item in items:\n",
" dict3[banci].setdefault(item,0)\n",
"\n",
"for k, v in dict1.items():\n",
" banci = v['banci']\n",
" #dict3.setdefault(unit,{})\n",
" #for item in items:\n",
" #dict3[unit].setdefault(v['level'],0)\n",
" if v['sex'] =='男':\n",
" dict3[banci][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": "code",
"execution_count": null,
"id": "1b2ebf62-9bf6-4c44-b2ec-ed9393c3c355",
"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_镇海2025.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"\n",
"dict3 = {}\n",
"\n",
"for k, v in dict1.items():\n",
" unit = v['banci']\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_沧州炼化-1.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/沧州炼化2025年体质检测明细表.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"title = ['编号', '姓名', '性别', '单位/部门', '年龄', '身高', '体重', 'bmi', '肺活量', '得分', '握力', '得分', '坐位体前屈', '得分', '纵跳', '得分', '俯卧撑', '得分', '单脚站立', '得分', '选择反应时', '得分', '台阶指数', '得分', '一分钟仰卧起坐', '得分', '中医体质', '是否倾向', '平和', '气虚', '阳虚', '阴虚', '痰湿', '湿热', '血瘀', '气郁', '特禀', '成就感', '愉快心理', '放松程度', '压力应对', '体力充沛', '情感充沛度', '颈椎', '胸椎', '腰椎', '骶尾椎']\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": "4d77aad2-5ae6-42a6-b5ed-eecefcdbfa50",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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