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512song@sina.com committed 2022-11-03 20:25:28 +08:00
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体测单位/巴陵石化.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "37eee6b1-ddbc-414c-ac74-e831c53c9bdb",
"metadata": {},
"source": [
"### 人员基本信息导入"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a27e986c-0c40-4792-b24d-03b19df707a9",
"metadata": {
"execution": {
"iopub.execute_input": "2022-11-03T12:05:14.162807Z",
"iopub.status.busy": "2022-11-03T12:05:14.162264Z",
"iopub.status.idle": "2022-11-03T12:05:15.514597Z",
"shell.execute_reply": "2022-11-03T12:05:15.513708Z",
"shell.execute_reply.started": "2022-11-03T12:05:14.162759Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"source": [
"import openpyxl\n",
"import json\n",
"\n",
"wb = openpyxl.load_workbook('data/巴陵石化监测花名册.xlsx')\n",
"sheet = wb.active\n",
"# sheets = wb.sheetnames\n",
"person = {}\n",
"for n in range(2, sheet.max_row+1):\n",
" if sheet.cell(n,2).value is None:\n",
" break\n",
" else: \n",
" code = int(sheet.cell(n, 4).value)\n",
" person.setdefault(code, {})\n",
" dict1 = {}\n",
" dict1['name'] = sheet.cell(n, 6).value \n",
" xb = str(sheet.cell(n, 7).value)\n",
" if xb == '1':\n",
" sex = '男'\n",
" elif xb =='2':\n",
" sex = '女'\n",
" dict1['sex'] = sex\n",
" dict1['unit'] = sheet.cell(n, 3).value\n",
" dict1['birth'] = str(sheet.cell(n,8).value).split(' ')[0]\n",
" person[code] = dict1\n",
"filename = 'data/巴陵石化人员.json'\n",
"with open(filename, 'w') as fl:\n",
" json.dump(person, fl, ensure_ascii=False)\n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "b1384a8f-36f4-483e-afb4-65a56a064dd3",
"metadata": {},
"source": [
"### 获取人员测试成绩"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "e5e4145b-d575-46b5-a530-c722668f76f3",
"metadata": {
"execution": {
"iopub.execute_input": "2022-11-03T12:04:52.389836Z",
"iopub.status.busy": "2022-11-03T12:04:52.389246Z",
"iopub.status.idle": "2022-11-03T12:04:52.901781Z",
"shell.execute_reply": "2022-11-03T12:04:52.900587Z",
"shell.execute_reply.started": "2022-11-03T12:04:52.389788Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ok\n"
]
}
],
"source": [
"import json\n",
"import time\n",
"import csv\n",
"\n",
"filename = '../item.json'\n",
"item = {}\n",
"unit = {}\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl) \n",
"for k,v in dict1.items():\n",
" item[k] = v\n",
"#SQL语句为：\n",
"# SELECT a.item_id,a.performance,a.score,a.date AS DATE1,a.avatar_id,b.unit,b.name FROM places_result AS a,_zgshhgxs AS b WHERE a.place_id=135 AND a.avatar_id=b.id AND a.avatar_id < 4999\n",
"\n",
"re_ta = {}\n",
"dict1 = {}\n",
"list1 = []\n",
"#print(\"\\n运动项目信息：\")\n",
"filename = 'data/137_2210.csv'\n",
"with open(filename,'r',newline='') as csv_file:\n",
" fl = csv.reader(csv_file,delimiter=',')\n",
" header = next(fl) \n",
" for line in fl:\n",
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
" list1.append(line)\n",
"#print(list1)\n",
"for result in list1:\n",
" user = str(result[4])\n",
" m_item = str(result[0]) \n",
" re_ta.setdefault(user,{}) \n",
" re_ta[user]['name'] = str(result[6])\n",
" re_ta[user]['unit'] = str(result[5]) \n",
" item_name = item[m_item]['name']\n",
" re_ta[user].setdefault(item_name,{}) \n",
" score = int(result[1])/item[m_item]['divisor'] \n",
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
" re_ta[user][item_name]['得分'] =result[2]\n",
"filename = 'data/result_巴陵.json'\n",
"with open(filename,'w') as fl:\n",
" json.dump(re_ta, fl) \n",
"print('ok')"
]
},
{
"cell_type": "markdown",
"id": "3c911994-2ce1-4412-8d56-39b195e66457",
"metadata": {},
"source": [
"### 导出测试成绩"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "0582bc84-7234-415f-9715-66c27b6b8f91",
"metadata": {
"execution": {
"iopub.execute_input": "2022-11-03T12:05:19.504467Z",
"iopub.status.busy": "2022-11-03T12:05:19.503886Z",
"iopub.status.idle": "2022-11-03T12:05:21.059764Z",
"shell.execute_reply": "2022-11-03T12:05:21.058715Z",
"shell.execute_reply.started": "2022-11-03T12:05:19.504418Z"
},
"tags": []
},
"outputs": [],
"source": [
"import json\n",
"import openpyxl\n",
"\n",
"items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"title = ['编号','姓名','性别','单位/部门','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
"filename = 'data/result_巴陵.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/巴陵石化人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
" \n",
"list1 = []\n",
"for k, v in dict1.items():\n",
" list2 = []\n",
" list2.append(str(k).rjust(5,'0'))\n",
" list2.append(v['name']) \n",
" list2.append(dict2[k]['sex'])\n",
" list2.append(dict2[k]['unit']) \n",
" \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 = 'data/巴陵石化体测情况表（截至20221103）.xlsx'\n",
"wb = openpyxl.Workbook()\n",
"sheet = wb.active\n",
"sheet.append(title)\n",
"for row in list1:\n",
" sheet.append(row)\n",
" \n",
"wb.save(filename)"
]
},
{
"cell_type": "markdown",
"id": "8e8dc85d-7ed7-4146-98c6-8d2dc64026ea",
"metadata": {},
"source": [
"### 统计测试成绩"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "6b40ff7f-68c1-4c04-9bdc-3af16980fc25",
"metadata": {
"execution": {
"iopub.execute_input": "2022-10-22T07:59:39.080864Z",
"iopub.status.busy": "2022-10-22T07:59:39.080347Z",
"iopub.status.idle": "2022-10-22T07:59:39.176961Z",
"shell.execute_reply": "2022-10-22T07:59:39.176140Z",
"shell.execute_reply.started": "2022-10-22T07:59:39.080817Z"
},
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"女 体重 2262 515\n",
"女 肺活量 1455 513\n",
"女 握力 1016 515\n",
"女 单脚站立 1389 513\n",
"女 纵跳 1324 510\n",
"女 一分钟仰卧起坐 1733 442\n",
"女 选择反应时 1667 509\n",
"女 坐位体前屈 1682 499\n",
"女 俯卧撑 0 499\n",
"女 台阶指数 1158 457\n",
"男 体重 4031 1114\n",
"男 肺活量 2967 1114\n",
"男 握力 2174 1118\n",
"男 单脚站立 2257 1096\n",
"男 纵跳 2426 1097\n",
"男 坐位体前屈 3310 1085\n",
"男 选择反应时 3714 1112\n",
"男 台阶指数 2282 949\n",
"男 俯卧撑 3192 1084\n",
"男 一分钟仰卧起坐 0 1084\n"
]
}
],
"source": [
"import json\n",
"import openpyxl\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",
"title = ['编号','姓名','性别','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",
"filename = 'data/result_巴陵.json'\n",
"with open(filename,'r') as fl:\n",
" dict1 = json.load(fl)\n",
"\n",
"filename = 'data/巴陵石化人员.json'\n",
"with open(filename,'r') as fl:\n",
" dict2 = json.load(fl)\n",
" \n",
"list1 = []\n",
"dict3 = {}\n",
"i = 0\n",
"for k, v in dict1.items():\n",
" sex = dict2[k]['sex']\n",
" dict3.setdefault(sex,{}) \n",
" for item in v.keys():\n",
" if item in items:\n",
" dict3[sex].setdefault(item,[]) \n",
" if v[item]['得分'].isdigit() :\n",
" dict3[sex][item].append(v[item]['得分']) \n",
"#print(dict3) \n",
"for k, v in dict3.items():\n",
" sex = k\n",
" for k1, v1 in v.items():\n",
" df = 0\n",
" if len(v1) >0:\n",
" \n",
" for i in range(0,len(v1)-1):\n",
" df = df + int(v1[i])\n",
" print(sex,k1,df,i)\n",
" \n",
" \n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4788ee4a-5b78-48ed-bfbf-dbf780baf569",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.8.10"
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"nbformat": 4,
"nbformat_minor": 5
}