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512song committed 2025-08-14 20:06:49 +08:00
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体测单位/南京化工.ipynb
+378 -50
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@@ -241,16 +241,9 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": null,
"id": "def3f47a-24ef-4815-b63b-2a16b79b4c15",
"metadata": {
"execution": {
"iopub.execute_input": "2025-08-13T08:03:28.281779Z",
"iopub.status.busy": "2025-08-13T08:03:28.281182Z",
"iopub.status.idle": "2025-08-13T08:03:28.305144Z",
"shell.execute_reply": "2025-08-13T08:03:28.304322Z",
"shell.execute_reply.started": "2025-08-13T08:03:28.281726Z"
},
"tags": []
},
"outputs": [],
@@ -304,17 +297,9 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": null,
"id": "8b7c0528-17b6-4469-b15f-3c4b794e286e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-08-13T08:04:18.256439Z",
"iopub.status.busy": "2025-08-13T08:04:18.255730Z",
"iopub.status.idle": "2025-08-13T08:04:18.280866Z",
"shell.execute_reply": "2025-08-13T08:04:18.280162Z",
"shell.execute_reply.started": "2025-08-13T08:04:18.256379Z"
}
},
"metadata": {},
"outputs": [],
"source": [
"import json\n",
@@ -440,6 +425,14 @@
" json.dump(dict1, fl, ensure_ascii=False)\n"
]
},
{
"cell_type": "markdown",
"id": "4930b4cb-2114-4432-a8ae-e6d2cde69b5c",
"metadata": {},
"source": [
"## 导入问卷信息(新)"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -453,22 +446,14 @@
"import time\n",
"from datetime import date\n",
"\n",
"dict1 = {}\n",
"\n",
"filename = 'data/result_南京化工.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"filename = 'data/南京化工人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict3 = json.load(fl)\n",
"\n",
"phone = {}\n",
"for k,v in dict3.items():\n",
" if 'phone' in v.keys():\n",
" phone[v['phone']] = k\n",
"\n",
"list1 = []\n",
"filename = 'data/survey_records_20250812.csv'\n",
"filename = 'data/survey_records_20250814.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
@@ -476,42 +461,33 @@
" list1.append(line)\n",
"\n",
"\n",
"\n",
"dict1 = {}\n",
"nn = 0\n",
"for item in list1: \n",
" \n",
" tcm = [] \n",
" \n",
" \n",
" for i in range(0,60):\n",
" tcm.append(0)\n",
" \n",
" content = json.loads(item[4]) \n",
" if int(content['phone']) in phone.keys(): \n",
" code = phone[int(content['phone'])]\n",
" print(code)\n",
" if code not in dict1.keys():\n",
" dict1[code] = dict3[code]\n",
" rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
" dict1[code]['rq'] = str(date.fromisoformat(item[5].replace('/','-').split(' ')[0]))\n",
" #dict1[code]['rq'] = item[5].replace('/','-').split(' ')[0]\n",
" else:\n",
" rq=date.fromisoformat('2025-08-12')\n",
" dict1[code]['rq'] = '2025-08-12'\n",
" for k, v in content.items():\n",
" phone = content['phone']\n",
" dict1.setdefault(phone,{})\n",
" \n",
" #rq = date.fromisoformat(item[5].replace('/','-').split(' ')[0])\n",
" #dict1[phone]['rq'] = str(date.fromisoformat(item[5].replace('/','-').split(' ')[0]))\n",
" \n",
" for k, v in content.items(): \n",
" if 'tcm' in k:\n",
" i = int(k[3:])\n",
" tcm[i-1] = int(v) \n",
" \n",
" if 'tcm' in item[4]: \n",
" dict1[code]['tcm'] = tcm\n",
" dict1[phone]['tcm'] = tcm\n",
" \n",
" birth = date.fromisoformat(dict3[code]['birth'].replace('/','-'))\n",
" \n",
" days = (rq-birth).days \n",
" dict1[code]['age'] = int(days/365)\n",
" dict1[code]['month'] = int(days/365*12)\n",
" dict1[phone]['name'] = content['name']\n",
" dict1[phone]['sex'] = content['gender']\n",
" dict1[phone]['weight'] = content['weight']\n",
" dict1[phone]['tun'] = content['hip']\n",
" dict1[phone]['yao'] = content['waist']\n",
" #print(phone[item[2]])\n",
" nn+=1\n",
"filename = 'data/result_南京化工-2.json'\n",
@@ -563,6 +539,178 @@
" json.dump(dict1, fl, ensure_ascii=False)\n"
]
},
{
"cell_type": "markdown",
"id": "19c6e8b6-2663-447d-884b-a22af3944c71",
"metadata": {
"jp-MarkdownHeadingCollapsed": true
},
"source": [
"## 计算中医体质并导出"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e233e6c3-9c3f-42c7-8057-012bbcfe8b26",
"metadata": {},
"outputs": [],
"source": [
"import openpyxl\n",
"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",
"\n",
"\n",
"filename = 'data/result_南京化工-2.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(v['weight'])\n",
" list3.append(v['yao'])\n",
" list3.append(v['tun'])\n",
" list3.append(kinds[kind])\n",
" list3.append(near)\n",
" for item in score:\n",
" list3.append(item)\n",
" list2.append(list3)\n",
"\n",
"filename = 'data/南化第二次问卷明细表.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"\n",
"for row in list2:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)\n",
"print('ok') "
]
},
{
"cell_type": "markdown",
"id": "caf77c95-3090-4fa1-bcec-c9e8a38d4ca9",
@@ -729,10 +877,190 @@
"print(i)"
]
},
{
"cell_type": "markdown",
"id": "42f1a67c-756a-4cf0-bd53-d71fb9c95aa6",
"metadata": {},
"source": [
"## 导入体检报告数据"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "c2fb2c7c-6541-4c41-ba38-0e1fee29aa97",
"metadata": {
"execution": {
"iopub.execute_input": "2025-08-14T11:18:53.769605Z",
"iopub.status.busy": "2025-08-14T11:18:53.769133Z",
"iopub.status.idle": "2025-08-14T11:18:53.803613Z",
"shell.execute_reply": "2025-08-14T11:18:53.803014Z",
"shell.execute_reply.started": "2025-08-14T11:18:53.769567Z"
}
},
"outputs": [],
"source": [
"from pathlib import Path\n",
"import json\n",
"import shutil\n",
"\n",
"\n",
"target_directory = Path('./data/json')\n",
"filename = 'data/南京化工人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"# 遍历目标目录及其子目录获取所有文件\n",
"dict2 = {}\n",
"list2 = ['总胆固醇','甘油三酯','尿微量白蛋白']\n",
"for fl in target_directory.glob('*.json'):\n",
" if fl.is_file():\n",
" code = fl.stem\n",
" dict2.setdefault(code,{})\n",
" dict2[code] = dict1[code]\n",
" with open(fl,'r') as fl1:\n",
" dict3 = json.load(fl1)\n",
" for k, v in dict3.items():\n",
" if k =='血压情况' and len(v)>0:\n",
" dict2[code].setdefault('血压',{})\n",
" list1 = [] \n",
" for item in v:\n",
" \n",
" dict2[code]['血压'][item['项目']] = item['结果']\n",
" if '状态' in item.keys():\n",
" list1.append(item['项目']+item['状态'])\n",
" if len(list1)>0:\n",
" dict2[code]['血压']['状态'] = ','.join(list1)\n",
" \n",
" if k in list2:\n",
" dict2[code].setdefault(k,{})\n",
" dict2[code][k]['结果'] = v['结果']\n",
" dict2[code][k]['参考值'] = v['参考值']\n",
" if '状态' in v.keys():\n",
" dict2[code][k]['状态'] = v['状态']\n",
" if k in ['空腹血糖','糖化血红蛋白']:\n",
" dict2[code].setdefault(k,{})\n",
" if '结果' in v.keys():\n",
" dict2[code][k]['结果'] = v['结果']\n",
" dict2[code][k]['参考值'] = v['参考值']\n",
" if '状态' in v.keys():\n",
" dict2[code][k]['状态'] = v['状态']\n",
" if k in ['ALT、AST、GGT','TSH、FT3、FT4']:\n",
" for item in v:\n",
" xm = item['项目']\n",
" dict2[code].setdefault(xm,{})\n",
" if '结果' in item.keys():\n",
" dict2[code][xm]['结果'] = item['结果']\n",
" if '参考值' in item.keys():\n",
" dict2[code][xm]['参考值'] = item['参考值']\n",
" if '状态' in item.keys():\n",
" dict2[code][xm]['状态'] = item['状态']\n",
" if k =='肾功能与尿微量白蛋白':\n",
" for item in v['肾功能']:\n",
" xm = item['项目']\n",
" dict2[code].setdefault(xm,{})\n",
" if '结果' in item.keys():\n",
" dict2[code][xm]['结果'] = item['结果']\n",
" if '参考值' in item.keys():\n",
" dict2[code][xm]['参考值'] = item['参考值']\n",
" if '状态' in item.keys():\n",
" dict2[code][xm]['状态'] = item['状态'] \n",
" dict2[code].setdefault('尿微量白蛋白',{})\n",
" xm = v['尿微量白蛋白']\n",
" if '结果' in xm.keys() and len(xm['结果'])>0:\n",
" dict2[code]['尿微量白蛋白']['结果'] = xm['结果']\n",
" if '参考值' in xm.keys() and len(xm['参考值'])>0:\n",
" dict2[code]['尿微量白蛋白']['参考值'] = xm['参考值']\n",
" if '状态' in xm.keys():\n",
" dict2[code]['尿微量白蛋白']['状态'] = xm['状态'] \n",
" \n",
" \n",
"\n",
"filename = 'data/南京化工体检情况.json'\n",
"\n",
"with open(filename,'w') as fl:\n",
" json.dump(dict2, fl, ensure_ascii=False) "
]
},
{
"cell_type": "markdown",
"id": "da43ceef-4215-4187-a76d-4e1434e50043",
"metadata": {},
"source": [
"## 导出体检报告数据"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "daa1b36e-1b62-49ee-9539-84c2d286fefe",
"metadata": {
"execution": {
"iopub.execute_input": "2025-08-14T11:19:18.851515Z",
"iopub.status.busy": "2025-08-14T11:19:18.850941Z",
"iopub.status.idle": "2025-08-14T11:19:18.941694Z",
"shell.execute_reply": "2025-08-14T11:19:18.941103Z",
"shell.execute_reply.started": "2025-08-14T11:19:18.851460Z"
}
},
"outputs": [],
"source": [
"import json\n",
"import csv\n",
"import openpyxl\n",
"\n",
"filename = 'data/南京化工体检情况.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"list1 = [\"总胆固醇\",\"甘油三酯\",\"空腹血糖\",\"糖化血红蛋白\",\"谷丙转氨酶 (ALT)\",\"谷草转氨酶 (AST)\",\"γ- 谷氨酰转肽酶 (GGT)\",\"促甲状腺激素 (TSH)\",\"游离三碘甲状腺原氨酸 (FT3)\",\"游离甲状腺素 (FT4)\",\"肌酐\",\"尿素氮\",\"尿酸\",\"尿微量白蛋白\"]\n",
"title = ['编号','姓名','性别','血压','状态']\n",
"for item in list1:\n",
" title.append(item)\n",
" title.append('状态')\n",
"list3 = []\n",
"for k, v in dict1.items():\n",
" list2 = []\n",
" list2.append(k)\n",
" list2.append(v['name'])\n",
" list2.append(v['sex'])\n",
" if '血压' in v.keys():\n",
" xueya = v['血压']['舒张压']+'/'+v['血压']['收缩压']\n",
" if '状态' in v['血压'].keys():\n",
" zt = v['血压']['状态']\n",
" else:\n",
" zt = ''\n",
" else:\n",
" xueya = ''\n",
" zt = ''\n",
" \n",
" list2.append(xueya)\n",
" list2.append(zt)\n",
" for item in list1:\n",
" if item in v.keys() and '结果' in v[item]:\n",
" list2.append(v[item]['结果'])\n",
" if '状态' in v[item]:\n",
" list2.append(v[item]['状态'])\n",
" else:\n",
" list2.append('')\n",
" else:\n",
" list2.append('')\n",
" list2.append('') \n",
" list3.append(list2)\n",
"\n",
"filename = 'data/南京化工体检相关数据明细.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list3:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "87556725-f68a-484b-827c-f6735155e940",
"id": "221b35dc-3a17-4950-993c-b634ee9a53cf",
"metadata": {},
"outputs": [],
"source": []