3431 lines
114 KiB
Plaintext
3431 lines
114 KiB
Plaintext
{
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"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e764be85-0ddf-4055-abd6-de2990e75db8",
|
||
"metadata": {
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||
"jp-MarkdownHeadingCollapsed": true,
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||
"tags": []
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},
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"source": [
|
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"# 第一次体测"
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]
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||
},
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||
{
|
||
"cell_type": "markdown",
|
||
"id": "ae533fe9-e20e-4e44-b9bb-030c4fa4e714",
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||
"metadata": {
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||
"tags": []
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},
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"source": [
|
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"## 体测人员导入"
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]
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||
},
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{
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||
"cell_type": "code",
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||
"execution_count": null,
|
||
"id": "1144aaac-92a0-4bcf-aba7-096f7dd3ad3b",
|
||
"metadata": {
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||
"tags": []
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||
},
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||
"outputs": [],
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||
"source": [
|
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"import openpyxl\n",
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"import json\n",
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"\n",
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"\n",
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"wb = openpyxl.load_workbook('data/天津石化员工检测花名册 （20221014）.xlsx')\n",
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"sheet = wb.active\n",
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"# sheets = wb.sheetnames\n",
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"person = {}\n",
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"\n",
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"for n in range(2, sheet.max_row+1):\n",
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" code = int(sheet.cell(n, 6).value)\n",
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" person.setdefault(code, {})\n",
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" dict1 = {}\n",
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" dict1['name'] = sheet.cell(n, 3).value\n",
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" dict1['sex'] = sheet.cell(n, 4).value\n",
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" dict1['unit'] = sheet.cell(n, 1).value\n",
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" dict1['sub_unit'] = sheet.cell(n, 2).value\n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['id_num'] = sheet.cell(n,5).value\n",
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" person[code] = dict1\n",
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"filename = 'data/天津石化人员名单.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(person, fl, ensure_ascii=False)\n",
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"print('ok')"
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]
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},
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{
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"cell_type": "markdown",
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||
"id": "93b9bfba-5404-4c9b-ac8f-48a3bf296669",
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"metadata": {},
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"source": [
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"## 合并人员信息"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d5171966-95ae-47ae-a75e-db08de772348",
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||
"metadata": {
|
||
"tags": []
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||
},
|
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"outputs": [],
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"source": [
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"import json\n",
|
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"filename = 'data/天津石化人员名单.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl)\n",
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"\n",
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"filename = 'data/天津石化人员231113_1.json'\n",
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"with open(filename,'r') as fl:\n",
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" dict2 = json.load(fl)\n",
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"\n",
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"for k, v in dict2.items():\n",
|
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" if k not in dict1.keys():\n",
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" dict1.setdefault(k,{})\n",
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" dict1[k]['name'] = dict2[k]['name']\n",
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" dict1[k]['sex'] = dict2[k]['sex']\n",
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" dict1[k]['unit'] = dict2[k]['name']\n",
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" dict1[k]['sub_unit'] = dict2[k]['sub_unit']\n",
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"filename = 'data/天津石化人员名单.json'\n",
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"with open(filename, 'w') as fl:\n",
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" json.dump(dict1, fl, ensure_ascii=False)\n",
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"print('ok')"
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]
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},
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{
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||
"cell_type": "markdown",
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||
"id": "5e648b69-40bf-4494-9079-e4e2b6ab8866",
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"metadata": {},
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"source": [
|
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"## 获取人员测试成绩"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a57ebb22-543c-4804-8d44-89984058ec1d",
|
||
"metadata": {
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||
"tags": []
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},
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"outputs": [],
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"source": [
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"import json\n",
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"import time\n",
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"import csv\n",
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"\n",
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"filename = '../item.json'\n",
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"item = {}\n",
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"unit = {}\n",
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"with open(filename,'r') as fl:\n",
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" dict1 = json.load(fl) \n",
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"for k,v in dict1.items():\n",
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" item[k] = v\n",
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"#SQL语句为：\n",
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"#SELECT a.item_id,a.performance,a.score,a.date AS DATE1,a.avatar_id,b.unit,b.name,a.date_joined FROM places_result AS a,_tianjin AS b WHERE a.place_id=134 AND a.avatar_id=b.id\n",
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"\n",
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"re_ta = {}\n",
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"dict1 = {}\n",
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"list1 = []\n",
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"#print(\"\\n运动项目信息：\")\n",
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"filename = '体测单位/data/20230428_134.csv'\n",
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"with open(filename,'r',newline='') as csv_file:\n",
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" fl = csv.reader(csv_file,delimiter=',')\n",
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" header = next(fl) \n",
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" for line in fl:\n",
|
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" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
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" list1.append(line)\n",
|
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"#print(list1)\n",
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"for result in list1:\n",
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" user = str(result[4])\n",
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" m_item = str(result[0]) \n",
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" re_ta.setdefault(user,{}) \n",
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" re_ta[user]['name'] = str(result[6])\n",
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" re_ta[user]['unit'] = str(result[5]) \n",
|
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" item_name = item[m_item]['name']\n",
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" re_ta[user].setdefault(item_name,{}) \n",
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" score = int(result[1])/item[m_item]['divisor'] \n",
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" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
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" re_ta[user][item_name]['得分'] =result[2]\n",
|
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"filename = 'data/result_天津.json'\n",
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"with open(filename,'w') as fl:\n",
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" json.dump(re_ta, fl) \n",
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"print('ok')"
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]
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},
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||
{
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||
"cell_type": "markdown",
|
||
"id": "55d961e5-a512-44b2-808e-7c55d7000d52",
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"metadata": {},
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||
"source": [
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"## 导出测试成绩"
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]
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},
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||
{
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"cell_type": "code",
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||
"execution_count": null,
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||
"id": "38397ad4-2bb3-4b5e-8ece-9ea11e801890",
|
||
"metadata": {
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||
"tags": []
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||
},
|
||
"outputs": [],
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||
"source": [
|
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"import json\n",
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"import openpyxl\n",
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"\n",
|
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"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",
|
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"title = ['编号','姓名','性别','单位/部门','车间/科室','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",
|
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"filename = 'data/result_天津.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
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" dict1 = json.load(fl)\n",
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"\n",
|
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"filename = 'data/天津石化人员名单.json'\n",
|
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"with open(filename,'r') as fl:\n",
|
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" dict2 = json.load(fl)\n",
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" \n",
|
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"list1 = []\n",
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"for k, v in dict1.items():\n",
|
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" list2 = []\n",
|
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" list2.append(str(k).rjust(8,'0'))\n",
|
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" list2.append(v['name']) \n",
|
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" list2.append(dict2[k]['sex'])\n",
|
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" list2.append(dict2[k]['unit'])\n",
|
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" list2.append(dict2[k]['sub_unit'])\n",
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" \n",
|
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" for item in items:\n",
|
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" if item in v.keys():\n",
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" list2.append(v[item]['成绩'])\n",
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" \n",
|
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" elif item =='name':\n",
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" list2.append(v[item])\n",
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" else:\n",
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" list2.append('') \n",
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" \n",
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" list1.append(list2)\n",
|
||
"filename = 'data/天津石化体测情况表（截至20221122）.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
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"sheet.append(title)\n",
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"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
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" \n",
|
||
"wb.save(filename)"
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||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "239ceb76-f690-4dae-991c-62c38d617c85",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 导出测试成绩(带得分)"
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||
]
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||
},
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||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "27529013-f3de-4e23-980d-f62203e4df88",
|
||
"metadata": {
|
||
"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','车间/科室','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_天津.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
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||
"\n",
|
||
"del dict1['1730253']\n",
|
||
"filename = 'data/天津石化人员名单.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
" \n",
|
||
"list1 = []\n",
|
||
"for k, v in dict1.items(): #print(k,dict2[str(k)]['name'])\n",
|
||
" list2 = []\n",
|
||
" list2.append(str(k).rjust(5,'0'))\n",
|
||
" list2.append(dict2[k]['name']) \n",
|
||
" list2.append(dict2[k]['sex'])\n",
|
||
" list2.append(dict2[k]['unit']) \n",
|
||
" list2.append(dict2[k]['sub_unit']) \n",
|
||
" for item in items:\n",
|
||
" if item in dict1[k].keys():\n",
|
||
" list2.append(dict1[k][item]['成绩'])\n",
|
||
" list2.append(dict1[k][item]['得分']) \n",
|
||
" elif item =='name':\n",
|
||
" list2.append(dict1[k][item])\n",
|
||
" else:\n",
|
||
" list2.append('') \n",
|
||
" list2.append('') \n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津石化体测情况表.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"sheet.append(title)\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok') "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1c7b219f-43cd-4bf0-971f-2c398f8db8ed",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 按照日期进行报告分类"
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||
]
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3d57ff66-69c3-4c13-811b-f1e13b404077",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 按照体测明细分类"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "29c0f15b-1345-4b46-ac1d-b45ddede9641",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import time\n",
|
||
"import csv\n",
|
||
"import os,sys,shutil\n",
|
||
"import glob\n",
|
||
"\n",
|
||
"dict1 = {}\n",
|
||
"list1 = []\n",
|
||
"filename = 'data/134_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",
|
||
"for result in list1:\n",
|
||
" user = str(result[4])\n",
|
||
" dict1.setdefault(user,'2022-10-01')\n",
|
||
" m_date = result[7]\n",
|
||
" if m_date> dict1[user]:\n",
|
||
" dict1[user] = m_date\n",
|
||
"\n",
|
||
"m_path = 'file/134'\n",
|
||
"\n",
|
||
"fls = glob.glob(f'file/new/*.pdf')\n",
|
||
"for fn in fls:\n",
|
||
" #old = os.path.basename(fn).split('.')[0].rjust(8,'0') \n",
|
||
" old = os.path.basename(fn).split('.')[0]\n",
|
||
" mrq = str(dict1[old]).split(' ')[0].replace('-', '', 2)\n",
|
||
" if not os.path.exists(m_path + '/new/' + mrq):\n",
|
||
" os.mkdir(m_path + '/new/' + mrq)\n",
|
||
" n_name = f'{m_path}/new/{mrq}/{str(old).rjust(8,\"0\")}_{mrq}.pdf'\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(fn,n_name)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ae2b17bd-38b9-4809-affb-01441a5581eb",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 按照报告生成日期分类"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "eb24c1be-b5d3-4e61-a432-854a887746d4",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import time\n",
|
||
"import csv\n",
|
||
"import os,sys,shutil\n",
|
||
"import glob\n",
|
||
"\n",
|
||
"dict1 = {}\n",
|
||
"list1 = []\n",
|
||
"\n",
|
||
"m_path = 'file/134'\n",
|
||
"mrq = '20221028'\n",
|
||
"if not os.path.exists(m_path + '/' + mrq):\n",
|
||
" os.mkdir(m_path + '/' + mrq)\n",
|
||
"fls = glob.glob(f'file/new/*.pdf')\n",
|
||
"for fn in fls:\n",
|
||
" #old = os.path.basename(fn).split('.')[0].rjust(8,'0') \n",
|
||
" old = os.path.basename(fn).split('.')[0] \n",
|
||
" n_name = f'{m_path}/{mrq}/{str(old).rjust(8,\"0\")}_{mrq}.pdf'\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(fn,n_name)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "d9061d26-b09b-4bff-af24-a14adda3d83f",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 按照部门报告分组"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "7ea2541f-461f-4eb5-860d-4b56d6be74ab",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import os,sys,shutil\n",
|
||
"import json\n",
|
||
"import math\n",
|
||
"import glob\n",
|
||
"from pathlib import Path\n",
|
||
"\n",
|
||
"fi_path = './file'\n",
|
||
"old = []\n",
|
||
"dict2 = {}\n",
|
||
"\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",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" m_name = v['name']\n",
|
||
" m_depart = v['unit'] \n",
|
||
" dict2[int(k)] = [m_name,m_depart]\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"fls = glob.glob(f'./file/*.pdf')\n",
|
||
"\n",
|
||
"for fn in fls:\n",
|
||
" old.append(os.path.basename(fn).split('.')[0])\n",
|
||
" #print(fn)\n",
|
||
"\n",
|
||
"\n",
|
||
"for n in old: \n",
|
||
" o_name = f'{fi_path}/{n}.pdf'\n",
|
||
" if not os.path.exists(f'{fi_path}/new/{dict2[int(n)][1]}'):\n",
|
||
" os.mkdir(f'{fi_path}/new/{dict2[int(n)][1]}') \n",
|
||
" n_name = f'{fi_path}/new/{dict2[int(n)][1]}/{str(n).rjust(5,\"0\")}-{dict2[int(n)][0]}.pdf'\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(o_name,n_name)\n",
|
||
" print(n_name)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "63eb8a23-4876-4be6-8800-1a67df8773ff",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import os,sys,shutil\n",
|
||
"import json\n",
|
||
"import math\n",
|
||
"import glob\n",
|
||
"from pathlib import Path\n",
|
||
"\n",
|
||
"fi_path = './file'\n",
|
||
"old = []\n",
|
||
"dict2 = {}\n",
|
||
"\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",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" m_name = v['name']\n",
|
||
" m_depart = v['unit'] \n",
|
||
" dict2[int(k)] = [m_name,m_depart]\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"fls = glob.glob(f'./file/*.pdf')\n",
|
||
"\n",
|
||
"for fn in fls:\n",
|
||
" old.append(os.path.basename(fn).split('.')[0])\n",
|
||
"\n",
|
||
"for n in old: \n",
|
||
" o_name = f'{fi_path}/{n}.pdf'\n",
|
||
" new_path = Path('file/new',dict1[n]['unit'],dict1[n]['sub_unit'])\n",
|
||
" new_path.mkdir(parents = True, exist_ok = True)\n",
|
||
" n_name = Path(new_path,f'{str(n).rjust(7,\"0\")}-{dict2[int(n)][0]}.pdf')\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(o_name,n_name)\n",
|
||
" print(n_name)\n",
|
||
" \n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e4590323-6645-450a-8055-756a5bf35b34",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 统计报告人员信息表"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "ed681a0d-4ee8-48ec-ab05-23da7156a44e",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"import os\n",
|
||
"import glob\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",
|
||
"m_path ='./file'\n",
|
||
"fls = glob.glob(f'file/*.pdf')\n",
|
||
"list1 = []\n",
|
||
"for fn in fls:\n",
|
||
" list2 = []\n",
|
||
" code = os.path.basename(fn).split('.')[0]\n",
|
||
" list2 = [code.rjust(7,\"0\"),dict1[code]['name'],dict1[code]['unit'],dict1[code]['sub_unit']]\n",
|
||
" list1.append(list2)\n",
|
||
"title = ['编号','姓名','单位/部门','车间/科室',] \n",
|
||
"filename = 'data/天津石化体测情况表.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"sheet.append(title)\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "838ec7d3-137c-4ccd-9f16-7b6312d1ffa6",
|
||
"metadata": {},
|
||
"source": [
|
||
"## PDF文件压缩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "a6ab0943-b018-4dd6-9176-85a762f9f60c",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import fitz\n",
|
||
"from pdf2image import convert_from_path, convert_from_bytes\n",
|
||
"import os,sys\n",
|
||
"import tempfile\n",
|
||
"from pdf2image.exceptions import (\n",
|
||
" PDFInfoNotInstalledError,\n",
|
||
" PDFPageCountError,\n",
|
||
" PDFSyntaxError\n",
|
||
")\n",
|
||
"import img2pdf \n",
|
||
"import glob\n",
|
||
"import shutil\n",
|
||
"\n",
|
||
"def covert2pic(old_fn):\n",
|
||
" if os.path.exists('.pdf'): # 临时文件，需为空\n",
|
||
" shutil.rmtree('.pdf')\n",
|
||
" os.mkdir('.pdf')\n",
|
||
" with tempfile.TemporaryDirectory() as path:\n",
|
||
" images_from_path = convert_from_path(old_fn, dpi=100,fmt='jpg', output_folder='.pdf')\n",
|
||
"\n",
|
||
"def pic2pdf(new_fn):\n",
|
||
" fl1=glob.glob('.pdf/*.jpg')\n",
|
||
" fl1.sort()\n",
|
||
" a4inpt = (img2pdf.mm_to_pt(210),img2pdf.mm_to_pt(297))\n",
|
||
" layout_fun = img2pdf.get_layout_fun(a4inpt)\n",
|
||
" with open(new_fn,\"wb\") as f:\n",
|
||
" f.write(img2pdf.convert(fl1,layout_fun=layout_fun))\n",
|
||
" print(f'{new_fn}转换成功！')\n",
|
||
" \n",
|
||
"\n",
|
||
"\n",
|
||
"def pdfz(sor, obj, zoom): \n",
|
||
" covert2pic(zoom)\n",
|
||
" pic2pdf(obj)\n",
|
||
" \n",
|
||
"fi_path = 'file/134/20221122/'\n",
|
||
"fl = glob.glob(f'{fi_path}*.pdf')\n",
|
||
"\n",
|
||
"for fn in fl:\n",
|
||
" new_fn = fi_path+'new/'+os.path.basename(fn)\n",
|
||
" covert2pic(fn)\n",
|
||
" pic2pdf(new_fn)\n",
|
||
" shutil.rmtree('.pdf')\n",
|
||
"print('ok!')\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a0cc9662-4171-4c2a-828d-f58c327ec8c1",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 统计未测试人员名单"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "daef91be-1b58-4fb1-b182-64f43c07c90f",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"title = ['编号','姓名','性别','单位/部门','车间/科室']\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",
|
||
"filename = 'data/result_天津.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",
|
||
" if k not in dict2.keys(): \n",
|
||
" list2 = [k,dict1[k]['name'],dict1[k]['sex'],dict1[k]['unit'],dict1[k]['sub_unit'],] \n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津石化未参加体测人数统计表.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": "72c693e1-dd7c-40fa-8948-4fd6fbea8ddc",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 区分新文件"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "9d06d4f0-364b-438c-844b-7d5badaf3496",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import os,sys,shutil\n",
|
||
"import glob\n",
|
||
"import time\n",
|
||
"\n",
|
||
"fi_path = 'file/'\n",
|
||
"fls = glob.glob(f'{fi_path}*.pdf')\n",
|
||
"m_date = time.strptime('2022-10-28','%Y-%m-%d')\n",
|
||
"for fn in fls:\n",
|
||
" c_time = time.gmtime(os.path.getctime(fn))\n",
|
||
" if c_time > m_date:\n",
|
||
" n_name = f'{fi_path}new/{os.path.basename(fn)}'\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(fn,n_name)\n",
|
||
" print(n_name)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "32b61559-4495-4fbe-8eb6-2614e6225b5c",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"title = ['编号','姓名','性别','单位/部门','车间/科室']\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",
|
||
"filename = 'data/result_天津.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"print(len(dict2),len(dict1),)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "47015abe-4cb8-436b-afa5-9ffd78d4a628",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 心理测试情况统计"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "c21efc40-2639-4b22-851f-925cd3f12d3a",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"title = ['编号','姓名','性别','单位/部门','车间/科室']\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",
|
||
"filename = 'data/134_xinli.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[4])\n",
|
||
"list3 = []\n",
|
||
"for k, v in dict1.items():\n",
|
||
" list2 = []\n",
|
||
" if k not in list1: \n",
|
||
" list2 = [k,dict1[k]['name'],dict1[k]['sex'],dict1[k]['unit'],dict1[k]['sub_unit'],] \n",
|
||
" list3.append(list2)\n",
|
||
"filename = 'data/天津石化未参加心理测试人数统计表.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)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "6b8ae75d-71a3-4cbe-a216-03c28d78156c",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"title = ['编号','姓名','性别','单位/部门','车间/科室']\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",
|
||
"list1 = []\n",
|
||
"filename = 'data/134_xinli.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",
|
||
" print(line[4])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "20e98f0d-61ea-43a5-8993-9656fed23099",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 体检报告统计分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0436a3a2-6230-43b3-beae-bc89e789b285",
|
||
"metadata": {},
|
||
"source": [
|
||
"### excel数据导入"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "7bb2e3aa-591d-4fce-983a-cde5d4c30e56",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import openpyxl\n",
|
||
"import json\n",
|
||
"import re\n",
|
||
"\n",
|
||
"wb = openpyxl.load_workbook('data/体检结果(模板)化工.xlsx')\n",
|
||
"sheet = wb.active\n",
|
||
"# sheets = wb.sheetnames\n",
|
||
"dict1 = {}\n",
|
||
"\n",
|
||
"for n in range(11, sheet.max_row+1):\n",
|
||
" code = sheet.cell(n, 1).value\n",
|
||
" name = sheet.cell(n, 8).value\n",
|
||
" txt = sheet[f'DT{str(n)}'].value \n",
|
||
" txt = re.sub(r'\\n', \"\", txt)\n",
|
||
" txt = re.sub(r'\\t', \"\", txt)\n",
|
||
" txt = re.sub(r'二、尊敬的顾客您好,您本次体检的建议信息如下：', \"\", txt)\n",
|
||
" ss = r'三、温馨提示： 鉴于医学技术发展的局限性，个体间可能存在的生物差异性以及您选择的检查项目的局限性，任何一次医学检查的手段和方法都不具备绝对的特异性和灵敏度，对于疾病筛检仍有其盲点，因此，我们建议您对本次检查的异常结果进行随诊复查和其他相关检查，以获得更可靠的医学证据建立准确地医学判断。'\n",
|
||
" txt1 = re.sub(r'三、温馨提示.*', \"\", txt,re.S)\n",
|
||
" dict1.setdefault(code, {})\n",
|
||
" dict1[code]['name'] = name\n",
|
||
" dict1[code]['xb'] = sheet.cell(n, 9).value\n",
|
||
" #dict1[code]['birth'] = sheet.cell(n, 10).value\n",
|
||
" dict1[code]['report'] = txt1\n",
|
||
"filename = 'data/体检结果.json'\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(dict1, fl, ensure_ascii=False) \n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "227a1c0b-fc78-4951-97ab-5664b59edd1d",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 体检结果分解"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "b38aef28-5d1b-4762-9c7e-70a531594fa4",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import openpyxl\n",
|
||
"import json\n",
|
||
"import re\n",
|
||
"\n",
|
||
"mo1 = r'[0-9]、'\n",
|
||
"mo2 = '【.*】'\n",
|
||
"filename = 'data/体检结果.json'\n",
|
||
"list3 = []\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"for k, v in dict1.items():\n",
|
||
" \n",
|
||
" ss = v['report']\n",
|
||
" list1 = re.split(mo1,ss)\n",
|
||
" if len(list1) ==1:\n",
|
||
" continue\n",
|
||
" else:\n",
|
||
" list1.remove('')\n",
|
||
" #print(list1)\n",
|
||
" for item in list1:\n",
|
||
" list2 = re.search( mo2, item)\n",
|
||
" xm =list2.group()\n",
|
||
" \n",
|
||
" txt = item.replace(xm,'').strip()\n",
|
||
" list3.append([k,v['name'],v['xb'],xm,txt])\n",
|
||
"filename = 'data/症状表.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"\n",
|
||
"for row in list3:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "964526bc-9c9c-4b63-9300-67b02d2608f5",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 天津人员制卡"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "83f02525-fd26-41ba-8b6a-c3cd584825e6",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import binascii\n",
|
||
"import openpyxl\n",
|
||
"gbs = 'C2EDC1A2D1C7'\n",
|
||
"bs = binascii.a2b_hex(gbs)\n",
|
||
"#print('bs', bs)\n",
|
||
"#print('decode-bs:', bs.decode('gb2312'))\n",
|
||
"\n",
|
||
"s = '马立亚'\n",
|
||
"gbcode = s.encode('gb2312') # 先转成 bytes格式\n",
|
||
"#print('gbcode:', gbcode)\n",
|
||
"gbs = \"\".join([hex(ch)[2:] for ch in gbcode]) #\n",
|
||
"#print('gbs:', gbs)\n",
|
||
"\n",
|
||
"wb = openpyxl.load_workbook('data/联合六车间体质测定人员名单.xlsx')\n",
|
||
"sheet = wb.active\n",
|
||
"# sheets = wb.sheetnames\n",
|
||
"person = {}\n",
|
||
"list1 = []\n",
|
||
"for n in range(3, sheet.max_row+1):\n",
|
||
" name = sheet.cell(n, 3).value\n",
|
||
" code = sheet.cell(n, 2).value\n",
|
||
" gbcode = code.encode('gbk')\n",
|
||
" code = \"\".join([hex(ch)[2:] for ch in gbcode])\n",
|
||
" gbcode = name.encode('gbk')\n",
|
||
" name = \"\".join([hex(ch)[2:] for ch in gbcode])\n",
|
||
" #for s in code:\n",
|
||
" # print(ord(s))\n",
|
||
" \n",
|
||
" list1.append([sheet.cell(n, 1).value,sheet.cell(n, 2).value,sheet.cell(n, 3).value,code.ljust(32,'0'),name.ljust(32,'0')])\n",
|
||
" print(code.ljust(32,'0'),name.ljust(32,'0'))\n",
|
||
"\n",
|
||
"filename = 'data/联合六车间体质测定人员制卡名单.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok!')\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "638bbe8e-3770-40e1-b884-ceeeec5a053c",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 因素分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9e25a7f2-0571-438b-9aa4-e3337d9fd840",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 清除修改测试项目"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "6e6f6a63-b297-42e8-a9ba-b2636fda5d09",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"code = '1734094'\n",
|
||
"items = ['身高','体重']\n",
|
||
"for item in items:\n",
|
||
" del dict1[code][item]\n",
|
||
"with open(filename, 'w') as fl:\n",
|
||
" json.dump(dict1, fl, ensure_ascii=False)\n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "f96b3aeb-bf37-4a8b-bf18-d0ae8f7df653",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 人员情况导入"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "4d77ec9b-c561-4355-98af-b18c42c1f3ca",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import openpyxl\n",
|
||
"import json\n",
|
||
"\n",
|
||
"\n",
|
||
"wb = openpyxl.load_workbook('data/员工个人基础信息20230113.xlsx')\n",
|
||
"sheet = wb.active\n",
|
||
"# sheets = wb.sheetnames\n",
|
||
"person = {}\n",
|
||
"\n",
|
||
"for n in range(4, sheet.max_row+1):\n",
|
||
" code = int(sheet.cell(n, 1).value)\n",
|
||
" person.setdefault(code, {})\n",
|
||
" dict1 = {}\n",
|
||
" dict1['name'] = sheet.cell(n, 2).value\n",
|
||
" dict1['sex'] = sheet.cell(n, 3).value\n",
|
||
" dict1['unit'] = sheet.cell(n, 6).value\n",
|
||
" dict1['sub_unit'] = sheet.cell(n, 7).value\n",
|
||
" if sheet.cell(n,10).value is not None:\n",
|
||
" dict1['daoban'] = '是'\n",
|
||
" else:\n",
|
||
" dict1['daoban'] = '否'\n",
|
||
" dict1['age'] = sheet.cell(n, 13).value\n",
|
||
" dict1['gl'] = sheet.cell(n, 14).value\n",
|
||
" dict1['jhgl'] = sheet.cell(n, 15).value \n",
|
||
" person[code] = dict1\n",
|
||
"filename = 'data/天津石化人员231113.json'\n",
|
||
"with open(filename, 'w') as fl:\n",
|
||
" json.dump(person, fl, ensure_ascii=False)\n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a5c58b77-69b6-4d76-8927-6e734556e848",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 人员体测得分导入合并"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "db473c01-7e1a-48c4-a0d7-e44cdeb9e24b",
|
||
"metadata": {
|
||
"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",
|
||
"\n",
|
||
"filename = 'data/result_天津.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"for k, v in dict2.items():\n",
|
||
" if k in dict1.keys():\n",
|
||
" for item in dict1[k].keys():\n",
|
||
" dict2[k][item] = dict1[k][item]\n",
|
||
"filename = 'data/天津石化人员231113.json'\n",
|
||
"with open(filename, 'w') as fl:\n",
|
||
" json.dump(dict2, fl, ensure_ascii=False)\n",
|
||
"print('ok')\n",
|
||
" "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "cc53ec68-cfc4-449a-9905-095a079dc8ab",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 筛选体测人员，计算得分"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "224cdee4-153f-424a-aaaa-92ef58943edb",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"items = ['体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n",
|
||
"\n",
|
||
"filename = 'data/result_天津.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"dict3 = {}\n",
|
||
"for k, v in dict2.items():\n",
|
||
" if k in dict1.keys():\n",
|
||
" dict3[k] = dict2[k]\n",
|
||
" i = 0\n",
|
||
" score =0\n",
|
||
" for item in dict2[k].keys(): \n",
|
||
" if item in items:\n",
|
||
" score = score + int(dict2[k][item]['得分'])\n",
|
||
" i+=1\n",
|
||
" dict3[k]['score'] = score\n",
|
||
" dict3[k]['item_num'] = i\n",
|
||
" dict3[k]['avg'] = round(score/i,2)\n",
|
||
"filename = 'data/天津石化线上测试结果.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"for k, v in dict2.items():\n",
|
||
" if k in dict1.keys():\n",
|
||
" dict3[k] = dict2[k]\n",
|
||
" dict3[k]['zhongyi'] = dict1[k]['中医体质']\n",
|
||
" \n",
|
||
"filename = 'data/天津石化人员231113_1.json'\n",
|
||
"with open(filename, 'w') as fl:\n",
|
||
" json.dump(dict3, fl, ensure_ascii=False)\n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "dd014e41-18f2-44e7-9f20-1190df4e7b45",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 因素分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c63bca31-f003-49e9-a20d-1931c050c740",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### 倒班因素分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "2a964412-8408-4039-a788-8cc1fc7cd518",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113_1.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"unit = set()\n",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit.add(dict1[k]['unit'])\n",
|
||
"#print(unit)\n",
|
||
"dict2 = {}\n",
|
||
"for k, v in dict1.items():\n",
|
||
" dict2.setdefault(v['unit'],{})\n",
|
||
" dict2[v['unit']].setdefault('是',{})\n",
|
||
" dict2[v['unit']].setdefault('否',{})\n",
|
||
" dict2[v['unit']]['是'].setdefault('num',0)\n",
|
||
" dict2[v['unit']]['否'].setdefault('num',0)\n",
|
||
" dict2[v['unit']]['是'].setdefault('score',0)\n",
|
||
" dict2[v['unit']]['否'].setdefault('score',0)\n",
|
||
" dict2[v['unit']]['是'].setdefault('zhongyi',0)\n",
|
||
" dict2[v['unit']]['否'].setdefault('zhongyi',0) \n",
|
||
" dict2[v['unit']]['是'].setdefault('pianpo',0)\n",
|
||
" dict2[v['unit']]['否'].setdefault('pianpo',0) \n",
|
||
" if 'avg' in v.keys():\n",
|
||
" dict2[v['unit']][v['daoban']]['num'] = dict2[v['unit']][v['daoban']]['num'] + 1\n",
|
||
" dict2[v['unit']][v['daoban']]['score'] = dict2[v['unit']][v['daoban']]['score'] + v['avg']\n",
|
||
" if 'zhongyi' in v.keys() :\n",
|
||
" dict2[v['unit']][v['daoban']]['zhongyi'] = dict2[v['unit']][v['daoban']]['zhongyi'] + 1\n",
|
||
" if 'zhongyi' in v.keys() and v['zhongyi']!='平和':\n",
|
||
" dict2[v['unit']][v['daoban']]['pianpo'] = dict2[v['unit']][v['daoban']]['pianpo'] + 1\n",
|
||
" \n",
|
||
" \n",
|
||
"for k, v in dict2.items(): \n",
|
||
" if v['是']['num'] > 0:\n",
|
||
" dict2[k]['是']['avg'] = round(v['是']['score']/v['是']['num'],2)\n",
|
||
" else:\n",
|
||
" dict2[k]['是']['avg'] = 0\n",
|
||
" if v['否']['num'] > 0:\n",
|
||
" dict2[k]['否']['avg'] = round(v['否']['score']/v['否']['num'],2)\n",
|
||
" else:\n",
|
||
" dict2[k]['否']['avg'] = 0\n",
|
||
"list1 = [] \n",
|
||
"for k, v in dict2.items():\n",
|
||
" list2 = []\n",
|
||
" unit = k\n",
|
||
" for k1, v1 in v.items():\n",
|
||
" daoban = k1\n",
|
||
" num = v1['num']\n",
|
||
" avg = v1['avg']\n",
|
||
" zhongyi = v1['zhongyi']\n",
|
||
" pianpo = v1['pianpo']\n",
|
||
" list2 = [k,daoban,num,avg,zhongyi,pianpo]\n",
|
||
" list1.append(list2)\n",
|
||
" \n",
|
||
"filename = 'data/天津倒班因素分析表.xlsx' \n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "2ccc4f6c-9cde-42d5-b41d-5b35ad86f042",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"source": [
|
||
"#### 工龄因素分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "695b4933-b8c3-4be6-a024-742a982f0abb",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113_1.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"unit = set()\n",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit.add(dict1[k]['unit'])\n",
|
||
"#print(unit)\n",
|
||
"dict2 = {}\n",
|
||
"for k, v in dict1.items():\n",
|
||
" gld = int(int(v['gl'])/10)\n",
|
||
" dict2.setdefault(gld,{})\n",
|
||
" dict2[gld].setdefault(v['sex'],{})\n",
|
||
" dict2[gld][v['sex']].setdefault('num',0)\n",
|
||
" dict2[gld][v['sex']].setdefault('score',0)\n",
|
||
" dict2[gld][v['sex']].setdefault('zhongyi',0)\n",
|
||
" dict2[gld][v['sex']].setdefault('pianpo',0) \n",
|
||
" if 'avg' in v.keys():\n",
|
||
" dict2[gld][v['sex']]['num'] = dict2[gld][v['sex']]['num'] + 1\n",
|
||
" dict2[gld][v['sex']]['score'] = dict2[gld][v['sex']]['score'] + v['avg']\n",
|
||
" if 'zhongyi' in v.keys() :\n",
|
||
" dict2[gld][v['sex']]['zhongyi'] = dict2[gld][v['sex']]['zhongyi'] + 1\n",
|
||
" if 'zhongyi' in v.keys() and v['zhongyi']!='平和':\n",
|
||
" dict2[gld][v['sex']]['pianpo'] = dict2[gld][v['sex']]['pianpo'] + 1\n",
|
||
"nl = {}\n",
|
||
"nl[0] = '工龄0-9年'\n",
|
||
"nl[1] = '工龄10-19年'\n",
|
||
"nl[2] = '工龄20-29年'\n",
|
||
"nl[3] = '工龄30-39年'\n",
|
||
"nl[4] = '工龄40-49年'\n",
|
||
"nl[5] = '工龄50年以上'\n",
|
||
"list1 = [] \n",
|
||
"for k, v in nl.items():\n",
|
||
" list2 = []\n",
|
||
" gld = v\n",
|
||
" for k1, v1 in dict2[k].items():\n",
|
||
" num = v1['num']\n",
|
||
" score = v1['score']\n",
|
||
" zhongyi = v1['zhongyi']\n",
|
||
" pianpo = v1['pianpo']\n",
|
||
" list2 = [k,daoban,num,avg,zhongyi,pianpo]\n",
|
||
" list1.append(list2)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "181ff60b-3372-441a-8cd7-29e8de66ceb8",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113_1.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"unit = set()\n",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit.add(dict1[k]['unit'])\n",
|
||
"#print(unit)\n",
|
||
"dict2 = {}\n",
|
||
"for k, v in dict1.items():\n",
|
||
" gld = int(int(v['gl'])/10)\n",
|
||
" dict2.setdefault(gld,{}) \n",
|
||
" dict2[gld].setdefault('num',0)\n",
|
||
" dict2[gld].setdefault('score',0)\n",
|
||
" dict2[gld].setdefault('zhongyi',0)\n",
|
||
" dict2[gld].setdefault('pianpo',0) \n",
|
||
" if 'avg' in v.keys():\n",
|
||
" dict2[gld]['num'] = dict2[gld]['num'] + 1\n",
|
||
" dict2[gld]['score'] = dict2[gld]['score'] + v['avg']\n",
|
||
" if 'zhongyi' in v.keys() :\n",
|
||
" dict2[gld]['zhongyi'] = dict2[gld]['zhongyi'] + 1\n",
|
||
" if 'zhongyi' in v.keys() and v['zhongyi']!='平和':\n",
|
||
" dict2[gld]['pianpo'] = dict2[gld]['pianpo'] + 1\n",
|
||
"print(dict2)\n",
|
||
"nl = {}\n",
|
||
"nl[0] = '工龄0-9年'\n",
|
||
"nl[1] = '工龄10-19年'\n",
|
||
"nl[2] = '工龄20-29年'\n",
|
||
"nl[3] = '工龄30-39年'\n",
|
||
"nl[4] = '工龄40-49年'\n",
|
||
"nl[5] = '工龄50年以上'\n",
|
||
"list1 = [] \n",
|
||
"for k, v in nl.items():\n",
|
||
" list2 = []\n",
|
||
" gld = v\n",
|
||
" \n",
|
||
" num = dict2[k]['num']\n",
|
||
" score = dict2[k]['score']\n",
|
||
" if num > 0:\n",
|
||
" avg = round(score/num,2)\n",
|
||
" else:\n",
|
||
" avg = 0\n",
|
||
" zhongyi = dict2[k]['zhongyi']\n",
|
||
" pianpo = dict2[k]['pianpo']\n",
|
||
" list2 = [gld,num,avg,zhongyi,pianpo]\n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津倒班因素分析表（工龄）.xlsx' \n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "f8fa3027-c88a-43a1-88c8-c6e9b7e94f91",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### 年龄因素分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "d5ab1a99-cb3e-4905-8c05-a6122ea09913",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113_1.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"unit = set()\n",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit.add(dict1[k]['unit'])\n",
|
||
"#print(unit)\n",
|
||
"dict2 = {}\n",
|
||
"for k, v in dict1.items():\n",
|
||
" gld = int(int(v['age'])/10)\n",
|
||
" dict2.setdefault(gld,{}) \n",
|
||
" dict2[gld].setdefault('num',0)\n",
|
||
" dict2[gld].setdefault('score',0)\n",
|
||
" dict2[gld].setdefault('zhongyi',0)\n",
|
||
" dict2[gld].setdefault('pianpo',0) \n",
|
||
" if 'avg' in v.keys():\n",
|
||
" dict2[gld]['num'] = dict2[gld]['num'] + 1\n",
|
||
" dict2[gld]['score'] = dict2[gld]['score'] + v['avg']\n",
|
||
" if 'zhongyi' in v.keys() :\n",
|
||
" dict2[gld]['zhongyi'] = dict2[gld]['zhongyi'] + 1\n",
|
||
" if 'zhongyi' in v.keys() and v['zhongyi']!='平和':\n",
|
||
" dict2[gld]['pianpo'] = dict2[gld]['pianpo'] + 1\n",
|
||
"nl = {}\n",
|
||
"\n",
|
||
"nl[2] = '20-29岁'\n",
|
||
"nl[3] = '30-39岁'\n",
|
||
"nl[4] = '40-49岁'\n",
|
||
"nl[5] = '50-59岁'\n",
|
||
"nl[6] = '60岁及以上'\n",
|
||
"list1 = [] \n",
|
||
"for k, v in nl.items():\n",
|
||
" list2 = []\n",
|
||
" gld = v\n",
|
||
" \n",
|
||
" num = dict2[k]['num']\n",
|
||
" score = dict2[k]['score']\n",
|
||
" if num > 0:\n",
|
||
" avg = round(score/num,2)\n",
|
||
" else:\n",
|
||
" avg = 0\n",
|
||
" zhongyi = dict2[k]['zhongyi']\n",
|
||
" pianpo = dict2[k]['pianpo']\n",
|
||
" list2 = [gld,num,avg,zhongyi,pianpo]\n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津倒班因素分析表（年龄）.xlsx' \n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "42e4ef5b-9aa8-4098-8f33-df9787dd34ab",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### 倒班时间因素分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "255b5649-fb85-424d-9fad-0f3e1dff2be3",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员231113_1.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"unit = set()\n",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit.add(dict1[k]['unit'])\n",
|
||
"#print(unit)\n",
|
||
"dict2 = {}\n",
|
||
"for k, v in dict1.items():\n",
|
||
" if v['daoban'] == '是':\n",
|
||
" \n",
|
||
" gld = int(int(v['gl'])/10)\n",
|
||
" dict2.setdefault(gld,{}) \n",
|
||
" dict2[gld].setdefault('num',0)\n",
|
||
" dict2[gld].setdefault('score',0)\n",
|
||
" dict2[gld].setdefault('zhongyi',0)\n",
|
||
" dict2[gld].setdefault('pianpo',0) \n",
|
||
" if 'avg' in v.keys():\n",
|
||
" dict2[gld]['num'] = dict2[gld]['num'] + 1\n",
|
||
" dict2[gld]['score'] = dict2[gld]['score'] + v['avg']\n",
|
||
" if 'zhongyi' in v.keys() :\n",
|
||
" dict2[gld]['zhongyi'] = dict2[gld]['zhongyi'] + 1\n",
|
||
" if 'zhongyi' in v.keys() and v['zhongyi']!='平和':\n",
|
||
" dict2[gld]['pianpo'] = dict2[gld]['pianpo'] + 1\n",
|
||
"print(dict2)\n",
|
||
"nl = {}\n",
|
||
"nl[0] = '倒班工龄0-9年'\n",
|
||
"nl[1] = '倒班工龄10-19年'\n",
|
||
"nl[2] = '倒班工龄20-29年'\n",
|
||
"nl[3] = '倒班工龄30-39年'\n",
|
||
"nl[4] = '倒班工龄40-49年'\n",
|
||
"list1 = [] \n",
|
||
"for k, v in nl.items():\n",
|
||
" list2 = []\n",
|
||
" gld = v\n",
|
||
" \n",
|
||
" num = dict2[k]['num']\n",
|
||
" score = dict2[k]['score']\n",
|
||
" if num > 0:\n",
|
||
" avg = round(score/num,2)\n",
|
||
" else:\n",
|
||
" avg = 0\n",
|
||
" zhongyi = dict2[k]['zhongyi']\n",
|
||
" pianpo = dict2[k]['pianpo']\n",
|
||
" list2 = [gld,num,avg,zhongyi,pianpo]\n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津倒班因素分析表（倒班工龄）.xlsx' \n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok!')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "73524e7f-4262-46d3-a733-74ac18e43855",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"source": [
|
||
"# 第二次体测"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1be2bf2c-b1c8-494b-bc6b-681b9e75d18d",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 体测人员导入"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "25283932-c03a-4a34-a59d-314fc64d8fbd",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import openpyxl\n",
|
||
"import json\n",
|
||
"\n",
|
||
"\n",
|
||
"wb = openpyxl.load_workbook('data/天津石化员工检测花名册（20230915）.xlsx')\n",
|
||
"sheet = wb.active\n",
|
||
"# sheets = wb.sheetnames\n",
|
||
"person = {}\n",
|
||
"\n",
|
||
"for n in range(2, sheet.max_row+1):\n",
|
||
" code = int(sheet.cell(n, 1).value)\n",
|
||
" person.setdefault(code, {})\n",
|
||
" dict1 = {}\n",
|
||
" dict1['name'] = sheet.cell(n, 2).value\n",
|
||
" dict1['sex'] = sheet.cell(n, 3).value\n",
|
||
" dict1['unit'] = sheet.cell(n, 5).value\n",
|
||
" dict1['sub_unit'] = sheet.cell(n, 6).value\n",
|
||
" dict1['birth'] = sheet.cell(n,4).value\n",
|
||
" person[code] = dict1\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename, 'w') as fl:\n",
|
||
" json.dump(person, fl, ensure_ascii=False)\n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "b758be8c-c9e2-46d4-b646-88403bb41e29",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 生产读卡系统文件"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "c908e5e7-c014-4b8d-a583-a8c2f7115a96",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"list1 = []\n",
|
||
"for k, v in dict1.items():\n",
|
||
" dict2 = {}\n",
|
||
" #if dict1['sex'] =='男':\n",
|
||
" # sex = 1\n",
|
||
" \n",
|
||
" dict2 = {'id':k,'name':v['name'],'gender':v['sex'],'birth':v['birth'],'unit':v['unit']}\n",
|
||
" list1.append(dict2)\n",
|
||
"json_data = json.dumps(list1,ensure_ascii=False, indent=4) \n",
|
||
"\n",
|
||
"# 将 json 数据写入文件\n",
|
||
"with open(\"data/data1.json\", \"w\",encoding = 'utf-8') as file:\n",
|
||
" file.write(json_data) \n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "60f4831c-b44e-40d2-ad8a-d79079c071f9",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 获取人员测试成绩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "e26b88fc-c75b-4c1e-82ea-5017370afa9b",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import time\n",
|
||
"import csv\n",
|
||
"\n",
|
||
"filename = '../item.json'\n",
|
||
"item = {}\n",
|
||
"unit = {}\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl) \n",
|
||
"for k,v in dict1.items():\n",
|
||
" item[k] = v\n",
|
||
"re_ta = {}\n",
|
||
"dict1 = {}\n",
|
||
"list1 = []\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl) \n",
|
||
"\n",
|
||
"filename = 'data/places_result_20231017.csv'\n",
|
||
"with open(filename,'r',newline='') as csv_file:\n",
|
||
" fl = csv.reader(csv_file,delimiter=',')\n",
|
||
" header = next(fl) \n",
|
||
" for line in fl:\n",
|
||
" #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n",
|
||
" list1.append(line)\n",
|
||
"#print(list1)\n",
|
||
"for result in list1:\n",
|
||
" user = str(result[2])\n",
|
||
" if user in dict1.keys(): \n",
|
||
" m_item = str(result[3]) \n",
|
||
" re_ta.setdefault(user,{}) \n",
|
||
" re_ta[user]['name'] = dict1[user]['name']\n",
|
||
" re_ta[user]['sex'] = dict1[user]['sex'] \n",
|
||
" re_ta[user]['unit'] = dict1[user]['unit']\n",
|
||
" re_ta[user]['sub_unit'] = dict1[user]['sub_unit']\n",
|
||
" item_name = item[m_item]['name']\n",
|
||
" re_ta[user].setdefault(item_name,{}) \n",
|
||
" score = int(result[4])/item[m_item]['divisor'] \n",
|
||
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
||
"print(len(re_ta))\n",
|
||
"filename = 'data/result_天津2023.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": "43bd1127-fa76-4c1e-8890-4bb47b28ecdf",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 导出测试人员信息"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "0a6ea33d-c112-4ed8-9366-3376e55a5731",
|
||
"metadata": {
|
||
"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",
|
||
"\n",
|
||
"filename = 'data/result_天津2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.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",
|
||
" list2.append(dict2[k]['sub_unit'])\n",
|
||
" for item in items:\n",
|
||
" if item in v.keys():\n",
|
||
" list2.append(v[item]['成绩']) \n",
|
||
" elif item =='name':\n",
|
||
" list2.append(v[item])\n",
|
||
" else:\n",
|
||
" list2.append('') \n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津石化体测情况（截至20231017）.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": "4a53db48-365e-4056-8468-bbc829e83682",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 统计各部门测试情况"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "589a5d44-605d-41a1-a981-7ec7258305ed",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"filename = 'data/result_天津2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"\n",
|
||
"dict3 = {}\n",
|
||
"for k, v in dict2.items():\n",
|
||
" unit = v['unit']\n",
|
||
" #sub_unit = v['sub_unit']\n",
|
||
" dict3.setdefault(unit,{})\n",
|
||
" dict3[unit].setdefault('人数',0)\n",
|
||
" #dict3[unit].setdefault(sub_unit,0)\n",
|
||
" #dict3[unit][sub_unit] = dict3[unit][sub_unit] + 1\n",
|
||
" dict3[unit]['人数'] = dict3[unit]['人数'] + 1\n",
|
||
"\n",
|
||
"title =['单位','体测人数']\n",
|
||
"list1 = []\n",
|
||
"for k,v in dict1.items(): \n",
|
||
" unit = v['unit']\n",
|
||
" #sub_unit = v['sub_unit']\n",
|
||
" #dict3[unit][sub_unit] = dict3[unit][sub_unit] - 1\n",
|
||
" dict3[unit]['人数'] = dict3[unit]['人数'] - 1\n",
|
||
"for k, v in dict3.items():\n",
|
||
" list2 = [k,v['人数']]\n",
|
||
" list1.append(list2)\n",
|
||
"\n",
|
||
"filename = 'data/天津部门未测试情况（截至20231013）.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": "d8e4038d-8ba0-48e7-b101-d30539cc2c2a",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 统计单一部门未体测人员明细表"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "2f7c9847-f283-4a09-b385-2c7559be7c7e",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/result_天津2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"unit_name = '炼油部'\n",
|
||
"rq = '20231008'\n",
|
||
"list1 = []\n",
|
||
"\n",
|
||
"i = 1\n",
|
||
"for k, v in dict2.items():\n",
|
||
" unit = v['unit']\n",
|
||
" if unit == unit_name and k not in dict1.keys():\n",
|
||
" list2 = [i,k,v['name'],unit,v['sub_unit']]\n",
|
||
" i+=1\n",
|
||
" list1.append(list2)\n",
|
||
"filename = f'data/天津石化{unit_name}未测试人员名单（截至{rq}）.xlsx'\n",
|
||
"title = ['序号','员工编号','姓名','部门','车间（科室）']\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": "a0754a83-0b8e-4bd8-9deb-b7d70a850f43",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 统计所有部门未体测人员明细表"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "e47c361d-a047-4932-b24e-fdcf65cb8a73",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/result_天津2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"unit = set()\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit.add(v['unit'])\n",
|
||
"rq = '20231013'\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"for unit_name in unit:\n",
|
||
" list1 = []\n",
|
||
"\n",
|
||
" i = 1\n",
|
||
" for k, v in dict2.items():\n",
|
||
" unit = v['unit']\n",
|
||
" if unit == unit_name and k not in dict1.keys():\n",
|
||
" list2 = [i,k,v['name'],unit,v['sub_unit']]\n",
|
||
" i+=1\n",
|
||
" list1.append(list2)\n",
|
||
" filename = f'data/天津石化{unit_name}未测试人员名单（截至{rq}）.xlsx'\n",
|
||
" title = ['序号','员工编号','姓名','部门','车间（科室）']\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)\n",
|
||
" wb.close\n",
|
||
" print(f'{unit_name}未测试人员名单（截至{rq}）生产成功！')\n",
|
||
"\n",
|
||
" "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6246f8b0-d9fc-4c9a-8ffa-07bd8dcdc3ed",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 统计未体测人员明细表"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "b7f62515-c45d-4d10-8e94-b5f9a9a98e3f",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"filename = 'data/result_天津2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"\n",
|
||
"list1 = []\n",
|
||
"\n",
|
||
"i = 1\n",
|
||
"for k, v in dict2.items():\n",
|
||
" \n",
|
||
" if k not in dict1.keys():\n",
|
||
" list2 = [i,k,v['name'],unit,v['sub_unit']]\n",
|
||
" i+=1\n",
|
||
" list1.append(list2)\n",
|
||
"filename = f'data/天津石化未测试人员名单.xlsx'\n",
|
||
"title = ['序号','员工编号','姓名','部门','车间（科室）']\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": "ed2a999f-47b9-4f36-88e2-354a0e37243b",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 转换报告格式"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "678ce52b-5368-4ec8-8b9e-0567895d856a",
|
||
"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/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl) \n",
|
||
"\n",
|
||
"filename = 'data/places_result_20231017.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",
|
||
" #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231017.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": "code",
|
||
"execution_count": null,
|
||
"id": "17a9248a-18b3-4696-a895-dde38f7f88a5",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import time\n",
|
||
"\n",
|
||
"filename = '../item.json'\n",
|
||
"item = {}\n",
|
||
"unit = {}\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict3 = json.load(fl) \n",
|
||
"for k,v in dict3.items():\n",
|
||
" item[k] = v\n",
|
||
"item['1']['en'] = 'lung'\n",
|
||
"item['2']['en'] = 'grip'\n",
|
||
"item['3']['en'] = 'flexion'\n",
|
||
"item['4']['en'] = 'jump'\n",
|
||
"item['5']['en'] = 'pushup'\n",
|
||
"item['6']['en'] = 'balance'\n",
|
||
"item['7']['en'] = 'reaction'\n",
|
||
"item['8']['en'] = 'step'\n",
|
||
"item['9']['en'] = 'situp'\n",
|
||
"item['10']['en'] = 'height'\n",
|
||
"item['11']['en'] = 'weight'\n",
|
||
"\n",
|
||
"filename = 'data/体质检测标准 (1).json' \n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"def cal_score(data1):\n",
|
||
" #data = {'name':'张三','sex':'M','age':37,'item':'StepExperiment','result':46} \n",
|
||
" person = dict1['person']\n",
|
||
" criteria = dict1['criteria']\n",
|
||
" if data1['age'] >59:\n",
|
||
" data1['age'] = 59\n",
|
||
" if data1['age'] <20:\n",
|
||
" data1['age'] = 20\n",
|
||
" info = data1['sex']+str(data1['age'])\n",
|
||
" bz = person[info]\n",
|
||
" mx = criteria[bz][data1['item']]\n",
|
||
" result = data1['result'] \n",
|
||
" if data1['item'] == 'reaction':\n",
|
||
" for bz1 in mx:\n",
|
||
" if result > bz1:\n",
|
||
" #print(bz1)\n",
|
||
" score = mx.index(bz1,0)\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" score = 5\n",
|
||
" else:\n",
|
||
" for bz1 in mx:\n",
|
||
" if result < bz1:\n",
|
||
" #print(bz1)\n",
|
||
" score = mx.index(bz1,0)\n",
|
||
" break\n",
|
||
" else:\n",
|
||
" score = 5\n",
|
||
" return(score)\n",
|
||
"filename = 'data/体质检测标准_BMI.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict4 = json.load(fl) \n",
|
||
" \n",
|
||
"def cal_bmi(data1):\n",
|
||
" # data = {'name':'张三','sex':'M','age':37,'item':'HeightWeight','result':'177.7,97.0'}\n",
|
||
" person = dict4['person']\n",
|
||
" criteria = dict4['criteria']\n",
|
||
" if data1['age'] > 59:\n",
|
||
" data1['age'] = 59\n",
|
||
" if data1['age'] <20:\n",
|
||
" data1['age'] = 20\n",
|
||
" info = data1['sex']+str(data1['age'])\n",
|
||
" bz = person[info]\n",
|
||
" #print(bz)\n",
|
||
" result = data1['result']\n",
|
||
" #print(data1['code'],result)\n",
|
||
" height = int(float(result.split(',')[0]))\n",
|
||
" weight = float(result.split(',')[1])\n",
|
||
" if str(height) not in criteria[bz]:\n",
|
||
" score = 1\n",
|
||
" else: \n",
|
||
" mx = criteria[bz][str(height)]\n",
|
||
" if weight < mx[0]:\n",
|
||
" score = 1\n",
|
||
" elif weight < mx[1]:\n",
|
||
" score = 3\n",
|
||
" elif weight < mx[2]:\n",
|
||
" score = 5 \n",
|
||
" elif weight <= mx[3]:\n",
|
||
" score = 3 \n",
|
||
" elif weight > mx[3]:\n",
|
||
" score = 1\n",
|
||
" return score\n",
|
||
" \n",
|
||
" \n",
|
||
"\n",
|
||
"#list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','height','weight']\n",
|
||
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp']\n",
|
||
"filename = 'data/result_天津231017.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_天津231017.json'\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(dict2,fl , ensure_ascii=False) \n",
|
||
"print('ok!') "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c1c98895-27e7-41c8-a43b-a63ebfa1c5e2",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 生成报告"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "f6171872-6b48-480a-b2c7-cf368d6cc6d8",
|
||
"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_天津231017.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"list1 = []\n",
|
||
"fiie_path ='./134/'\n",
|
||
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
|
||
"i=1\n",
|
||
"list2 = []\n",
|
||
"for k, v in dict1.items():\n",
|
||
" list1 = []\n",
|
||
" mydata = {}\n",
|
||
" \n",
|
||
" id = str(k).rjust(8,\"0\")\n",
|
||
" mydata['path'] = fiie_path+id+'-'+ v['name']+'.pdf'\n",
|
||
" mydata['title'] = '中石化(天津)石油化工有限公司'\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",
|
||
" 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'][item] = {'mark':mark,'score':v[item]['score']}\n",
|
||
" if len(mydata['fits']) >2:\n",
|
||
" \n",
|
||
" list1.append(mydata)\n",
|
||
" list2.append([k,v['name']])\n",
|
||
" i+=1\n",
|
||
" #x = requests.post('http://192.168.31.163:3003', data = json.dumps(list1), headers=headers)\n",
|
||
" print(id,v['name'],x.text)\n",
|
||
" #x.close()\n",
|
||
"print(i)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "489fdbe1-30ed-4630-b2fa-d926e41bdcc9",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 核对报告人数"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "906fa6c6-3446-4176-a443-fe16e52a8a3a",
|
||
"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-old2/134'\n",
|
||
"\n",
|
||
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
||
"\n",
|
||
"filename = 'data/result_天津231017.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\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,v['name'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "cb587095-1a0c-4ab1-b9e5-e9e5b0d52cee",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 报告按部门分类"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "3fa6a1a9-63af-4f4e-9d30-b94f4357f7dc",
|
||
"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-old2/134'\n",
|
||
"new_path = 'file/134'\n",
|
||
"old = []\n",
|
||
"dict2 = {}\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
||
"for fn in fls:\n",
|
||
" fi_name =Path(fn).stem.split('-')[0]\n",
|
||
" code = int(fi_name)\n",
|
||
" unit_path = Path(new_path,dict1[str(code)]['unit'])\n",
|
||
" unit_path.mkdir(parents = True, exist_ok = True)\n",
|
||
" n_name = Path(unit_path,Path(fn).stem+'.pdf')\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(fn,n_name)\n",
|
||
" #print(n_name)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "fdcd8ea1-21ab-48ab-b7cc-0dad65b06bf2",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 生成体测报告打印明细表"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "623671be-cef0-4a2c-bf1a-889ab159760f",
|
||
"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-old2/134'\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
||
"list1 = []\n",
|
||
"for fn in fls:\n",
|
||
" list2 = []\n",
|
||
" fi_name =Path(fn).stem.split('-')[0] \n",
|
||
" code = int(fi_name)\n",
|
||
" unit = dict1[str(code)]['unit']\n",
|
||
" list2 = [fi_name,Path(fn).stem.split('-')[1],unit]\n",
|
||
" \n",
|
||
" list1.append(list2)\n",
|
||
"print(list1)\n",
|
||
"filename = 'data/天津石化体测报告打印明细表.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": "4a075c1b-41d9-4ff5-8f0a-115127e5e155",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 生成体测成绩明细表"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "b363792b-cbc6-46a7-b87f-1e122bcb116e",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"items = ['lung','grip','flexion','jump','pushup','situp','balance','reaction','step']\n",
|
||
"bmi = ['height','weight']\n",
|
||
"title = ['编号','姓名','性别','单位/部门','身高','体重','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",
|
||
"\n",
|
||
"filename = 'data/result_天津231017.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"list1 = []\n",
|
||
"for k, v in dict1.items(): #print(k,dict2[str(k)]['name'])\n",
|
||
" list2 = []\n",
|
||
" list2.append(str(k).rjust(5,'0'))\n",
|
||
" list2.append(dict1[k]['name']) \n",
|
||
" list2.append(dict1[k]['sex'])\n",
|
||
" list2.append(dict1[k]['unit'])\n",
|
||
" i = 0\n",
|
||
" if 'bmi' in dict1[k].keys():\n",
|
||
" list2.append(dict1[k]['height']['成绩'])\n",
|
||
" list2.append(dict1[k]['weight']['成绩'])\n",
|
||
" list2.append(dict1[k]['bmi']['score'])\n",
|
||
" i+=1\n",
|
||
" else:\n",
|
||
" list2.append('') \n",
|
||
" list2.append('') \n",
|
||
" list2.append('') \n",
|
||
" \n",
|
||
" \n",
|
||
" for item in items:\n",
|
||
" if item in dict1[k].keys():\n",
|
||
" list2.append(dict1[k][item]['成绩'])\n",
|
||
" list2.append(dict1[k][item]['score']) \n",
|
||
" i+=1\n",
|
||
" elif item =='name':\n",
|
||
" list2.append(dict1[k][item])\n",
|
||
" else:\n",
|
||
" list2.append('') \n",
|
||
" list2.append('') \n",
|
||
" if i>2:\n",
|
||
" list1.append(list2)\n",
|
||
"filename = 'data/天津石化体测情况表.xlsx'\n",
|
||
"wb = openpyxl.Workbook()\n",
|
||
"sheet = wb.active\n",
|
||
"sheet.append(title)\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)\n",
|
||
"print('ok') "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "5608369a-f33f-4c02-a68f-f4f7bb410069",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 生成新格式文件"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 209,
|
||
"id": "8397633f-fddb-4cfa-b9bd-e38f3fe6772c",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-07T15:21:25.620601Z",
|
||
"iopub.status.busy": "2023-11-07T15:21:25.620142Z",
|
||
"iopub.status.idle": "2023-11-07T15:21:26.613442Z",
|
||
"shell.execute_reply": "2023-11-07T15:21:26.612982Z",
|
||
"shell.execute_reply.started": "2023-11-07T15:21:25.620564Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import os,sys,shutil\n",
|
||
"import json\n",
|
||
"import glob\n",
|
||
"from pathlib import Path\n",
|
||
"\n",
|
||
"fi_path = '/home/songyi/pdf-typescript-old2/134'\n",
|
||
"new_path = 'file/134_1'\n",
|
||
"old = []\n",
|
||
"filename = 'data/result_天津231017.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"fls = glob.glob(f'{fi_path}/*.pdf')\n",
|
||
"i =0\n",
|
||
"for fn in fls:\n",
|
||
" code =str(int(Path(fn).stem.split('-')[0]))\n",
|
||
" if code in dict1.keys():\n",
|
||
" i+=1\n",
|
||
" #print(i,code,dict1[code]['rq'].replace('-',''))\n",
|
||
" \n",
|
||
" n_name = Path(new_path,code.rjust(8,'0')+'_'+dict1[code]['rq'].replace('-','')+'.pdf')\n",
|
||
" #print(i,n_name)\n",
|
||
" if not os.path.exists(n_name):\n",
|
||
" shutil.copyfile(fn,n_name)\n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "85a03b00-9624-4ae9-aa6d-386798d457df",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-10-25T02:50:56.997544Z",
|
||
"iopub.status.busy": "2023-10-25T02:50:56.995911Z",
|
||
"iopub.status.idle": "2023-10-25T02:50:57.006678Z",
|
||
"shell.execute_reply": "2023-10-25T02:50:57.004773Z",
|
||
"shell.execute_reply.started": "2023-10-25T02:50:56.997463Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"source": [
|
||
"# 体测数据分析"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "dca06570-73e6-4f60-8cf9-b3f9da64f1c4",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 清理报告数据"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "f9fee64f-41ff-4453-8a32-a33df086022e",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"import openpyxl\n",
|
||
"\n",
|
||
"\n",
|
||
"filename = 'data/result_天津231017.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 ='./134/'\n",
|
||
"list_item = ['lung','grip','flexion','jump','pushup','balance','reaction','step','situp','bmi']\n",
|
||
"i=1\n",
|
||
"list2 = []\n",
|
||
"dict2 = {}\n",
|
||
"for k, v in dict1.items():\n",
|
||
" list1 = []\n",
|
||
" mydata = {}\n",
|
||
" \n",
|
||
" id = str(k).rjust(8,\"0\")\n",
|
||
" mydata['unit'] = v['unit']\n",
|
||
" mydata['name'] = v['name']\n",
|
||
" mydata['sex'] = v['sex']\n",
|
||
" mydata['month'] = v['month']\n",
|
||
" age = int(v['month']/12)\n",
|
||
" if age <20:\n",
|
||
" mydata['age'] = 20\n",
|
||
" else:\n",
|
||
" mydata['age'] = int(v['month']/12)\n",
|
||
" \n",
|
||
" mydata['fits'] = {}\n",
|
||
" score = 0\n",
|
||
" for item in list_item:\n",
|
||
" if item in v.keys():\n",
|
||
" if item in ['lung','pushup','step','situp']:\n",
|
||
" mark = v[item]['成绩'].split()[0].split('.')[0]\n",
|
||
" else:\n",
|
||
" mark = v[item]['成绩'].split()[0]\n",
|
||
" mydata['fits'][items[item]] = {'mark':mark,'score':v[item]['score']}\n",
|
||
" score = score + v[item]['score']\n",
|
||
" mydata['score'] = round(score/len(mydata['fits']),2)\n",
|
||
" if len(mydata['fits']) >2:\n",
|
||
" dict2[str(k)] = mydata\n",
|
||
"filename = f'data/data_天津231017.json'\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(dict2,fl , ensure_ascii=False) \n",
|
||
"print('ok!') "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "bd1f8f42-c14a-4bb7-8656-14a0f7968cfc",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 计算测试等级"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 210,
|
||
"id": "006afc6c-2b1f-4edf-be1b-5f60e2029ee8",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-08T09:26:45.377399Z",
|
||
"iopub.status.busy": "2023-11-08T09:26:45.376933Z",
|
||
"iopub.status.idle": "2023-11-08T09:26:45.467443Z",
|
||
"shell.execute_reply": "2023-11-08T09:26:45.467001Z",
|
||
"shell.execute_reply.started": "2023-11-08T09:26:45.377362Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"0~255分人数：2524人,男性：2056人,女性:468人\n",
|
||
"256~332分人数：2214人,男性：1400人,女性:814人\n",
|
||
"333~367分人数：495人,男性：274人,女性:221人\n",
|
||
"368~500分人数：150人,男性：58人,女性:92人\n",
|
||
"5383\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_天津231017.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))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ed3c0653-087a-4a9d-ba21-8cf5f48515d9",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 根据年龄汇总人员信息及成绩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "949e4c3c-023d-44a4-b99e-c5460da61161",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"nld = [[20,24],[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 = 1\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",
|
||
" \n",
|
||
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i-1}人,男性：{m}人')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6a967a44-7c12-4e82-827b-d75926c09e77",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 根据年龄汇总人员信息及成绩（男）"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "721977d3-5816-4bf6-82fc-26fd170e5454",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
||
"\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl) \n",
|
||
"for item in nld:\n",
|
||
" di = item[0]\n",
|
||
" gao = item[1]\n",
|
||
" i = 1\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",
|
||
" \n",
|
||
" \n",
|
||
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i-1}人')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3a8f747e-aacd-45bf-b94a-b505cfd31922",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 根据年龄汇总人员信息及成绩（女）"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "f493dc0a-d3cd-4dbd-ad35-e06eb96afbc5",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
||
"\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl) \n",
|
||
"for item in nld:\n",
|
||
" di = item[0]\n",
|
||
" gao = item[1]\n",
|
||
" i = 1\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",
|
||
" \n",
|
||
" \n",
|
||
" print(f'{di}~{gao}岁平均成绩：{round(score/i,2)}分，人数：{i-1}人')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e9c6bd2e-b6ac-4a6f-ba28-aafcabb40c0d",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 计算平均成绩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "7155f2c2-0719-4558-aa3b-629fb70194d6",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"nld = [[20,24],[25,29],[30,34],[35,39],[40,44],[45,49],[50,54],[55,80]]\n",
|
||
"#filename = 'data/result_石家庄.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/5383,4)}分，总体：5383人')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9a544eec-ec58-47dc-aa36-d890b0b309c2",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 计算测试等级"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "a0bbb339-ee4e-4dc1-83ec-b2055e3c670e",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import json\n",
|
||
"\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",
|
||
"\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",
|
||
"#filename = 'data/result_石家庄.json'\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(dict1, fl) \n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "92103efb-a3e4-43ec-acfb-e4cb0b07c2fb",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 计算各年龄段测试等级(女）"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 216,
|
||
"id": "f8949993-7501-4359-aa7c-2cd5de348056",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-08T12:59:02.064806Z",
|
||
"iopub.status.busy": "2023-11-08T12:59:02.064358Z",
|
||
"iopub.status.idle": "2023-11-08T12:59:02.302186Z",
|
||
"shell.execute_reply": "2023-11-08T12:59:02.301753Z",
|
||
"shell.execute_reply.started": "2023-11-08T12:59:02.064771Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"0~255分人数：2524人,男性：468人,女性:2056人\n",
|
||
"256~332分人数：2214人,男性：814人,女性:1400人\n",
|
||
"333~367分人数：495人,男性：221人,女性:274人\n",
|
||
"368~500分人数：150人,男性：92人,女性:58人\n",
|
||
"ok\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import json\n",
|
||
"\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",
|
||
"\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'] == '女':\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",
|
||
"#filename = 'data/result_石家庄.json'\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(dict1, fl) \n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "5a130857-4dd1-4b5e-b21b-42fe32b367cf",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 按部门统计"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "cb1e13ae-3eba-4f6e-b70a-2bf87168ef1a",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 计算部门完成情况"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 225,
|
||
"id": "5e7c1c49-75bf-4238-9bd7-b8511687f639",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-08T14:05:30.666811Z",
|
||
"iopub.status.busy": "2023-11-08T14:05:30.666354Z",
|
||
"iopub.status.idle": "2023-11-08T14:05:30.762473Z",
|
||
"shell.execute_reply": "2023-11-08T14:05:30.762012Z",
|
||
"shell.execute_reply.started": "2023-11-08T14:05:30.666775Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'消防支队': {'应测': 93, '已测': 72}, '电仪部': {'应测': 352, '已测': 322}, '水务部': {'应测': 441, '已测': 396}, '烯烃部': {'应测': 359, '已测': 320}, '热电部': {'应测': 500, '已测': 412}, '炼油部': {'应测': 1276, '已测': 1191}, '化工部': {'应测': 609, '已测': 522}, '运输销售部': {'应测': 225, '已测': 199}, '化验计量部': {'应测': 549, '已测': 469}, '南港烯烃部': {'应测': 779, '已测': 681}, '公司机关': {'应测': 409, '已测': 112}, '信息档案管理中心': {'应测': 77, '已测': 60}, '装备研究院': {'应测': 57, '已测': 48}, '原油储运部': {'应测': 203, '已测': 178}, '党委党校（培训中心）': {'应测': 81, '已测': 48}, '研究院': {'应测': 110, '已测': 101}, '南港乙烯项目管理部': {'应测': 71, '已测': 15}, '行政事务中心': {'应测': 134, '已测': 41}, '聚醚部': {'应测': 153, '已测': 112}, '物资采购中心': {'应测': 198, '已测': 84}}\n",
|
||
"消防支队 93 72\n",
|
||
"电仪部 352 322\n",
|
||
"水务部 441 396\n",
|
||
"烯烃部 359 320\n",
|
||
"热电部 500 412\n",
|
||
"炼油部 1276 1191\n",
|
||
"化工部 609 522\n",
|
||
"运输销售部 225 199\n",
|
||
"化验计量部 549 469\n",
|
||
"南港烯烃部 779 681\n",
|
||
"公司机关 409 112\n",
|
||
"信息档案管理中心 77 60\n",
|
||
"装备研究院 57 48\n",
|
||
"原油储运部 203 178\n",
|
||
"党委党校（培训中心） 81 48\n",
|
||
"研究院 110 101\n",
|
||
"南港乙烯项目管理部 71 15\n",
|
||
"行政事务中心 134 41\n",
|
||
"聚醚部 153 112\n",
|
||
"物资采购中心 198 84\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import json\n",
|
||
"\n",
|
||
"\n",
|
||
"filename = 'data/data_天津231017.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"dict3 = {}\n",
|
||
"\n",
|
||
"for k, v in dict2.items():\n",
|
||
" unit = v['unit']\n",
|
||
" dict3.setdefault(unit,{})\n",
|
||
" dict3[unit].setdefault('应测',0)\n",
|
||
" dict3[unit].setdefault('已测',0)\n",
|
||
" dict3[unit]['应测']+=1\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit = v['unit']\n",
|
||
" \n",
|
||
" dict3[unit]['已测']+=1\n",
|
||
" \n",
|
||
"print(dict3)\n",
|
||
"for k ,v in dict3.items():\n",
|
||
" print(k,v['应测'],v['已测'])\n",
|
||
" "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e83941b9-b2b5-41db-b08a-a619f07c2487",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-08T13:52:50.838712Z",
|
||
"iopub.status.busy": "2023-11-08T13:52:50.838249Z",
|
||
"iopub.status.idle": "2023-11-08T13:52:50.844168Z",
|
||
"shell.execute_reply": "2023-11-08T13:52:50.843014Z",
|
||
"shell.execute_reply.started": "2023-11-08T13:52:50.838676Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"source": [
|
||
"### 计算部门合格率"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 226,
|
||
"id": "d023724c-46b7-4b4e-bbcc-8b4f171590c5",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-08T14:05:37.421932Z",
|
||
"iopub.status.busy": "2023-11-08T14:05:37.421639Z",
|
||
"iopub.status.idle": "2023-11-08T14:05:37.428753Z",
|
||
"shell.execute_reply": "2023-11-08T14:05:37.428329Z",
|
||
"shell.execute_reply.started": "2023-11-08T14:05:37.421910Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'消防支队': {'应测': 93, '已测': 72, '合格': 35, '不合格': 33, '良好': 3, '优秀': 1}, '电仪部': {'应测': 352, '已测': 322, '不合格': 182, '良好': 18, '合格': 118, '优秀': 4}, '水务部': {'应测': 441, '已测': 396, '不合格': 202, '合格': 150, '良好': 37, '优秀': 7}, '烯烃部': {'应测': 359, '已测': 320, '不合格': 143, '合格': 124, '良好': 37, '优秀': 16}, '热电部': {'应测': 500, '已测': 412, '不合格': 185, '良好': 51, '合格': 157, '优秀': 19}, '炼油部': {'应测': 1276, '已测': 1191, '合格': 514, '不合格': 518, '良好': 126, '优秀': 33}, '化工部': {'应测': 609, '已测': 522, '不合格': 243, '良好': 54, '合格': 206, '优秀': 19}, '运输销售部': {'应测': 225, '已测': 199, '合格': 63, '不合格': 120, '良好': 11, '优秀': 5}, '化验计量部': {'应测': 549, '已测': 469, '合格': 195, '良好': 39, '不合格': 226, '优秀': 9}, '南港烯烃部': {'应测': 779, '已测': 681, '不合格': 345, '良好': 28, '合格': 304, '优秀': 4}, '公司机关': {'应测': 409, '已测': 112, '合格': 44, '不合格': 47, '优秀': 3, '良好': 18}, '信息档案管理中心': {'应测': 77, '已测': 60, '不合格': 16, '合格': 32, '优秀': 2, '良好': 10}, '装备研究院': {'应测': 57, '已测': 48, '不合格': 20, '合格': 20, '良好': 6, '优秀': 2}, '原油储运部': {'应测': 203, '已测': 178, '不合格': 86, '良好': 10, '合格': 79, '优秀': 3}, '党委党校（培训中心）': {'应测': 81, '已测': 48, '不合格': 16, '良好': 11, '合格': 19, '优秀': 2}, '研究院': {'应测': 110, '已测': 101, '优秀': 7, '不合格': 35, '合格': 45, '良好': 14}, '南港乙烯项目管理部': {'应测': 71, '已测': 15, '不合格': 6, '合格': 8, '良好': 1}, '行政事务中心': {'应测': 134, '已测': 41, '不合格': 20, '良好': 5, '合格': 15, '优秀': 1}, '聚醚部': {'应测': 153, '已测': 112, '不合格': 48, '合格': 47, '良好': 10, '优秀': 7}, '物资采购中心': {'应测': 198, '已测': 84, '不合格': 33, '合格': 39, '优秀': 6, '良好': 6}}\n",
|
||
"消防支队 72 33\n",
|
||
"电仪部 322 182\n",
|
||
"水务部 396 202\n",
|
||
"烯烃部 320 143\n",
|
||
"热电部 412 185\n",
|
||
"炼油部 1191 518\n",
|
||
"化工部 522 243\n",
|
||
"运输销售部 199 120\n",
|
||
"化验计量部 469 226\n",
|
||
"南港烯烃部 681 345\n",
|
||
"公司机关 112 47\n",
|
||
"信息档案管理中心 60 16\n",
|
||
"装备研究院 48 20\n",
|
||
"原油储运部 178 86\n",
|
||
"党委党校（培训中心） 48 16\n",
|
||
"研究院 101 35\n",
|
||
"南港乙烯项目管理部 15 6\n",
|
||
"行政事务中心 41 20\n",
|
||
"聚醚部 112 48\n",
|
||
"物资采购中心 84 33\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"for k, v in dict1.items():\n",
|
||
" unit = v['unit']\n",
|
||
" dict3[unit].setdefault(v['level'],0)\n",
|
||
" dict3[unit][v['level']]+=1\n",
|
||
"print(dict3)\n",
|
||
"for k ,v in dict3.items():\n",
|
||
" print(k,v['已测'],v['不合格'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "4b996a8a-70e7-4c95-8b14-0f8fa89df7a4",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 计算部门成绩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 228,
|
||
"id": "1d93d58e-115a-44a4-988f-fa5353c5fd0e",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-11-08T14:26:34.150100Z",
|
||
"iopub.status.busy": "2023-11-08T14:26:34.149698Z",
|
||
"iopub.status.idle": "2023-11-08T14:26:34.216125Z",
|
||
"shell.execute_reply": "2023-11-08T14:26:34.215668Z",
|
||
"shell.execute_reply.started": "2023-11-08T14:26:34.150070Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{'化验计量部': {'BMI': {'score': 1724, 'count': 464}, '肺活量': {'score': 1482, 'count': 447}, '握力': {'score': 546, 'count': 445}, '坐位体前屈': {'score': 969, 'count': 373}, '纵跳': {'score': 659, 'count': 375}, '俯卧撑': {'score': 408, 'count': 165}, '一分钟仰卧起坐': {'score': 486, 'count': 131}, '单脚站立': {'score': 896, 'count': 443}, '选择反应时': {'score': 1266, 'count': 447}, '台阶指数': {'score': 366, 'count': 143}}, '南港烯烃部': {'BMI': {'score': 2220, 'count': 680}, '肺活量': {'score': 2389, 'count': 674}, '握力': {'score': 753, 'count': 664}, '坐位体前屈': {'score': 1747, 'count': 631}, '纵跳': {'score': 1324, 'count': 630}, '俯卧撑': {'score': 1140, 'count': 444}, '一分钟仰卧起坐': {'score': 548, 'count': 144}, '单脚站立': {'score': 1189, 'count': 665}, '选择反应时': {'score': 1770, 'count': 678}, '台阶指数': {'score': 802, 'count': 381}}, '消防支队': {'BMI': {'score': 258, 'count': 72}, '肺活量': {'score': 228, 'count': 72}, '握力': {'score': 92, 'count': 71}, '坐位体前屈': {'score': 169, 'count': 60}, '纵跳': {'score': 86, 'count': 62}, '俯卧撑': {'score': 154, 'count': 51}, '一分钟仰卧起坐': {'score': 22, 'count': 7}, '单脚站立': {'score': 129, 'count': 67}, '选择反应时': {'score': 213, 'count': 70}, '台阶指数': {'score': 69, 'count': 26}}, '炼油部': {'BMI': {'score': 4052, 'count': 1178}, '肺活量': {'score': 3865, 'count': 1181}, '握力': {'score': 2106, 'count': 1184}, '坐位体前屈': {'score': 3324, 'count': 1075}, '纵跳': {'score': 2208, 'count': 1044}, '俯卧撑': {'score': 1730, 'count': 761}, '一分钟仰卧起坐': {'score': 778, 'count': 210}, '单脚站立': {'score': 2154, 'count': 1155}, '选择反应时': {'score': 3554, 'count': 1175}, '台阶指数': {'score': 1441, 'count': 542}}, '化工部': {'BMI': {'score': 1824, 'count': 516}, '肺活量': {'score': 1578, 'count': 508}, '握力': {'score': 630, 'count': 517}, '坐位体前屈': {'score': 1323, 'count': 431}, '纵跳': {'score': 822, 'count': 430}, '俯卧撑': {'score': 699, 'count': 295}, '一分钟仰卧起坐': {'score': 367, 'count': 94}, '单脚站立': {'score': 1030, 'count': 499}, '选择反应时': {'score': 1535, 'count': 512}, '台阶指数': {'score': 508, 'count': 175}}, '电仪部': {'BMI': {'score': 1088, 'count': 322}, '肺活量': {'score': 1054, 'count': 317}, '握力': {'score': 394, 'count': 319}, '坐位体前屈': {'score': 734, 'count': 284}, '纵跳': {'score': 500, 'count': 299}, '俯卧撑': {'score': 561, 'count': 223}, '一分钟仰卧起坐': {'score': 183, 'count': 50}, '单脚站立': {'score': 575, 'count': 319}, '选择反应时': {'score': 827, 'count': 318}, '台阶指数': {'score': 452, 'count': 178}}, '物资采购中心': {'BMI': {'score': 289, 'count': 83}, '肺活量': {'score': 280, 'count': 83}, '握力': {'score': 93, 'count': 82}, '坐位体前屈': {'score': 207, 'count': 69}, '纵跳': {'score': 143, 'count': 79}, '俯卧撑': {'score': 96, 'count': 36}, '一分钟仰卧起坐': {'score': 108, 'count': 26}, '单脚站立': {'score': 184, 'count': 77}, '选择反应时': {'score': 260, 'count': 81}, '台阶指数': {'score': 76, 'count': 27}}, '水务部': {'BMI': {'score': 1381, 'count': 395}, '肺活量': {'score': 1242, 'count': 386}, '握力': {'score': 488, 'count': 394}, '坐位体前屈': {'score': 876, 'count': 313}, '纵跳': {'score': 556, 'count': 315}, '俯卧撑': {'score': 522, 'count': 199}, '一分钟仰卧起坐': {'score': 257, 'count': 65}, '单脚站立': {'score': 788, 'count': 382}, '选择反应时': {'score': 1182, 'count': 391}, '台阶指数': {'score': 305, 'count': 116}}, '运输销售部': {'BMI': {'score': 723, 'count': 197}, '肺活量': {'score': 570, 'count': 186}, '握力': {'score': 249, 'count': 192}, '坐位体前屈': {'score': 401, 'count': 138}, '纵跳': {'score': 236, 'count': 158}, '俯卧撑': {'score': 263, 'count': 123}, '一分钟仰卧起坐': {'score': 97, 'count': 23}, '单脚站立': {'score': 328, 'count': 183}, '选择反应时': {'score': 584, 'count': 195}, '台阶指数': {'score': 68, 'count': 24}}, '原油储运部': {'BMI': {'score': 600, 'count': 176}, '肺活量': {'score': 574, 'count': 175}, '握力': {'score': 215, 'count': 176}, '坐位体前屈': {'score': 378, 'count': 146}, '纵跳': {'score': 291, 'count': 154}, '俯卧撑': {'score': 268, 'count': 105}, '一分钟仰卧起坐': {'score': 133, 'count': 37}, '单脚站立': {'score': 355, 'count': 174}, '选择反应时': {'score': 503, 'count': 177}, '台阶指数': {'score': 193, 'count': 79}}, '聚醚部': {'BMI': {'score': 407, 'count': 109}, '肺活量': {'score': 378, 'count': 107}, '握力': {'score': 149, 'count': 109}, '坐位体前屈': {'score': 280, 'count': 100}, '纵跳': {'score': 176, 'count': 100}, '俯卧撑': {'score': 136, 'count': 56}, '一分钟仰卧起坐': {'score': 114, 'count': 27}, '单脚站立': {'score': 209, 'count': 108}, '选择反应时': {'score': 345, 'count': 110}, '台阶指数': {'score': 105, 'count': 36}}, '公司机关': {'BMI': {'score': 416, 'count': 112}, '肺活量': {'score': 381, 'count': 112}, '握力': {'score': 125, 'count': 108}, '坐位体前屈': {'score': 272, 'count': 101}, '纵跳': {'score': 220, 'count': 100}, '俯卧撑': {'score': 160, 'count': 53}, '一分钟仰卧起坐': {'score': 120, 'count': 30}, '单脚站立': {'score': 225, 'count': 106}, '选择反应时': {'score': 310, 'count': 110}, '台阶指数': {'score': 135, 'count': 51}}, '南港乙烯项目管理部': {'BMI': {'score': 65, 'count': 15}, '肺活量': {'score': 58, 'count': 15}, '握力': {'score': 13, 'count': 13}, '坐位体前屈': {'score': 34, 'count': 13}, '纵跳': {'score': 27, 'count': 15}, '俯卧撑': {'score': 39, 'count': 13}, '一分钟仰卧起坐': {'score': 0, 'count': 0}, '单脚站立': {'score': 20, 'count': 15}, '选择反应时': {'score': 40, 'count': 15}, '台阶指数': {'score': 29, 'count': 10}}, '党委党校（培训中心）': {'BMI': {'score': 192, 'count': 48}, '肺活量': {'score': 161, 'count': 44}, '握力': {'score': 43, 'count': 43}, '坐位体前屈': {'score': 119, 'count': 40}, '纵跳': {'score': 80, 'count': 44}, '俯卧撑': {'score': 44, 'count': 18}, '一分钟仰卧起坐': {'score': 59, 'count': 15}, '单脚站立': {'score': 101, 'count': 42}, '选择反应时': {'score': 159, 'count': 48}, '台阶指数': {'score': 53, 'count': 18}}, '装备研究院': {'BMI': {'score': 202, 'count': 48}, '肺活量': {'score': 175, 'count': 48}, '握力': {'score': 57, 'count': 48}, '坐位体前屈': {'score': 122, 'count': 46}, '纵跳': {'score': 93, 'count': 45}, '俯卧撑': {'score': 57, 'count': 25}, '一分钟仰卧起坐': {'score': 45, 'count': 10}, '单脚站立': {'score': 99, 'count': 47}, '选择反应时': {'score': 145, 'count': 48}, '台阶指数': {'score': 33, 'count': 13}}, '热电部': {'BMI': {'score': 1457, 'count': 411}, '肺活量': {'score': 1332, 'count': 404}, '握力': {'score': 593, 'count': 407}, '坐位体前屈': {'score': 932, 'count': 333}, '纵跳': {'score': 693, 'count': 335}, '俯卧撑': {'score': 689, 'count': 255}, '一分钟仰卧起坐': {'score': 164, 'count': 42}, '单脚站立': {'score': 781, 'count': 390}, '选择反应时': {'score': 1231, 'count': 407}, '台阶指数': {'score': 386, 'count': 135}}, '烯烃部': {'BMI': {'score': 1173, 'count': 317}, '肺活量': {'score': 993, 'count': 318}, '握力': {'score': 426, 'count': 318}, '坐位体前屈': {'score': 779, 'count': 256}, '纵跳': {'score': 509, 'count': 266}, '俯卧撑': {'score': 409, 'count': 165}, '一分钟仰卧起坐': {'score': 257, 'count': 65}, '单脚站立': {'score': 647, 'count': 311}, '选择反应时': {'score': 983, 'count': 317}, '台阶指数': {'score': 332, 'count': 117}}, '行政事务中心': {'BMI': {'score': 157, 'count': 41}, '肺活量': {'score': 111, 'count': 36}, '握力': {'score': 53, 'count': 40}, '坐位体前屈': {'score': 78, 'count': 32}, '纵跳': {'score': 68, 'count': 40}, '俯卧撑': {'score': 65, 'count': 19}, '一分钟仰卧起坐': {'score': 64, 'count': 15}, '单脚站立': {'score': 83, 'count': 39}, '选择反应时': {'score': 121, 'count': 41}, '台阶指数': {'score': 51, 'count': 19}}, '信息档案管理中心': {'BMI': {'score': 245, 'count': 59}, '肺活量': {'score': 219, 'count': 59}, '握力': {'score': 63, 'count': 60}, '坐位体前屈': {'score': 162, 'count': 53}, '纵跳': {'score': 103, 'count': 56}, '俯卧撑': {'score': 73, 'count': 25}, '一分钟仰卧起坐': {'score': 86, 'count': 21}, '单脚站立': {'score': 146, 'count': 59}, '选择反应时': {'score': 189, 'count': 59}, '台阶指数': {'score': 98, 'count': 34}}, '研究院': {'BMI': {'score': 405, 'count': 101}, '肺活量': {'score': 346, 'count': 98}, '握力': {'score': 132, 'count': 101}, '坐位体前屈': {'score': 245, 'count': 87}, '纵跳': {'score': 166, 'count': 85}, '俯卧撑': {'score': 170, 'count': 54}, '一分钟仰卧起坐': {'score': 92, 'count': 22}, '单脚站立': {'score': 213, 'count': 99}, '选择反应时': {'score': 337, 'count': 101}, '台阶指数': {'score': 119, 'count': 40}}}\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",
|
||
"filename = 'data/data_天津231017.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict1 = json.load(fl)\n",
|
||
"\n",
|
||
"filename = 'data/天津石化人员名单2023.json'\n",
|
||
"with open(filename,'r') as fl:\n",
|
||
" dict2 = json.load(fl)\n",
|
||
"dict3 = {}\n",
|
||
"\n",
|
||
"for k, v in dict1.items():\n",
|
||
" unit = v['unit']\n",
|
||
" dict3.setdefault(unit,{})\n",
|
||
" for item in items:\n",
|
||
" dict3[unit].setdefault(item,{})\n",
|
||
" dict3[unit][item].setdefault('score',0)\n",
|
||
" dict3[unit][item].setdefault('count',0)\n",
|
||
" for k1,v1 in v['fits'].items():\n",
|
||
" if k1 in items:\n",
|
||
" dict3[unit][k1]['score']+=v1['score']\n",
|
||
" dict3[unit][k1]['count']+=1\n",
|
||
"print(dict3)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "23a654a2-69f1-41cb-b3dc-23bc7dc7e294",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 显示部门成绩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 236,
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"化验计量部\n",
|
||
"BMI 3.7155\n",
|
||
"肺活量 3.3154\n",
|
||
"握力 1.227\n",
|
||
"坐位体前屈 2.5979\n",
|
||
"纵跳 1.7573\n",
|
||
"俯卧撑 2.4727\n",
|
||
"一分钟仰卧起坐 3.7099\n",
|
||
"单脚站立 2.0226\n",
|
||
"选择反应时 2.8322\n",
|
||
"台阶指数 2.5594\n",
|
||
"\n",
|
||
"南港烯烃部\n",
|
||
"BMI 3.2647\n",
|
||
"肺活量 3.5445\n",
|
||
"握力 1.134\n",
|
||
"坐位体前屈 2.7686\n",
|
||
"纵跳 2.1016\n",
|
||
"俯卧撑 2.5676\n",
|
||
"一分钟仰卧起坐 3.8056\n",
|
||
"单脚站立 1.788\n",
|
||
"选择反应时 2.6106\n",
|
||
"台阶指数 2.105\n",
|
||
"\n",
|
||
"消防支队\n",
|
||
"BMI 3.5833\n",
|
||
"肺活量 3.1667\n",
|
||
"握力 1.2958\n",
|
||
"坐位体前屈 2.8167\n",
|
||
"纵跳 1.3871\n",
|
||
"俯卧撑 3.0196\n",
|
||
"一分钟仰卧起坐 3.1429\n",
|
||
"单脚站立 1.9254\n",
|
||
"选择反应时 3.0429\n",
|
||
"台阶指数 2.6538\n",
|
||
"\n",
|
||
"炼油部\n",
|
||
"BMI 3.4397\n",
|
||
"肺活量 3.2727\n",
|
||
"握力 1.7787\n",
|
||
"坐位体前屈 3.0921\n",
|
||
"纵跳 2.1149\n",
|
||
"俯卧撑 2.2733\n",
|
||
"一分钟仰卧起坐 3.7048\n",
|
||
"单脚站立 1.8649\n",
|
||
"选择反应时 3.0247\n",
|
||
"台阶指数 2.6587\n",
|
||
"\n",
|
||
"化工部\n",
|
||
"BMI 3.5349\n",
|
||
"肺活量 3.1063\n",
|
||
"握力 1.2186\n",
|
||
"坐位体前屈 3.0696\n",
|
||
"纵跳 1.9116\n",
|
||
"俯卧撑 2.3695\n",
|
||
"一分钟仰卧起坐 3.9043\n",
|
||
"单脚站立 2.0641\n",
|
||
"选择反应时 2.998\n",
|
||
"台阶指数 2.9029\n",
|
||
"\n",
|
||
"电仪部\n",
|
||
"BMI 3.3789\n",
|
||
"肺活量 3.3249\n",
|
||
"握力 1.2351\n",
|
||
"坐位体前屈 2.5845\n",
|
||
"纵跳 1.6722\n",
|
||
"俯卧撑 2.5157\n",
|
||
"一分钟仰卧起坐 3.66\n",
|
||
"单脚站立 1.8025\n",
|
||
"选择反应时 2.6006\n",
|
||
"台阶指数 2.5393\n",
|
||
"\n",
|
||
"物资采购中心\n",
|
||
"BMI 3.4819\n",
|
||
"肺活量 3.3735\n",
|
||
"握力 1.1341\n",
|
||
"坐位体前屈 3.0\n",
|
||
"纵跳 1.8101\n",
|
||
"俯卧撑 2.6667\n",
|
||
"一分钟仰卧起坐 4.1538\n",
|
||
"单脚站立 2.3896\n",
|
||
"选择反应时 3.2099\n",
|
||
"台阶指数 2.8148\n",
|
||
"\n",
|
||
"水务部\n",
|
||
"BMI 3.4962\n",
|
||
"肺活量 3.2176\n",
|
||
"握力 1.2386\n",
|
||
"坐位体前屈 2.7987\n",
|
||
"纵跳 1.7651\n",
|
||
"俯卧撑 2.6231\n",
|
||
"一分钟仰卧起坐 3.9538\n",
|
||
"单脚站立 2.0628\n",
|
||
"选择反应时 3.023\n",
|
||
"台阶指数 2.6293\n",
|
||
"\n",
|
||
"运输销售部\n",
|
||
"BMI 3.6701\n",
|
||
"肺活量 3.0645\n",
|
||
"握力 1.2969\n",
|
||
"坐位体前屈 2.9058\n",
|
||
"纵跳 1.4937\n",
|
||
"俯卧撑 2.1382\n",
|
||
"一分钟仰卧起坐 4.2174\n",
|
||
"单脚站立 1.7923\n",
|
||
"选择反应时 2.9949\n",
|
||
"台阶指数 2.8333\n",
|
||
"\n",
|
||
"原油储运部\n",
|
||
"BMI 3.4091\n",
|
||
"肺活量 3.28\n",
|
||
"握力 1.2216\n",
|
||
"坐位体前屈 2.589\n",
|
||
"纵跳 1.8896\n",
|
||
"俯卧撑 2.5524\n",
|
||
"一分钟仰卧起坐 3.5946\n",
|
||
"单脚站立 2.0402\n",
|
||
"选择反应时 2.8418\n",
|
||
"台阶指数 2.443\n",
|
||
"\n",
|
||
"聚醚部\n",
|
||
"BMI 3.7339\n",
|
||
"肺活量 3.5327\n",
|
||
"握力 1.367\n",
|
||
"坐位体前屈 2.8\n",
|
||
"纵跳 1.76\n",
|
||
"俯卧撑 2.4286\n",
|
||
"一分钟仰卧起坐 4.2222\n",
|
||
"单脚站立 1.9352\n",
|
||
"选择反应时 3.1364\n",
|
||
"台阶指数 2.9167\n",
|
||
"\n",
|
||
"公司机关\n",
|
||
"BMI 3.7143\n",
|
||
"肺活量 3.4018\n",
|
||
"握力 1.1574\n",
|
||
"坐位体前屈 2.6931\n",
|
||
"纵跳 2.2\n",
|
||
"俯卧撑 3.0189\n",
|
||
"一分钟仰卧起坐 4.0\n",
|
||
"单脚站立 2.1226\n",
|
||
"选择反应时 2.8182\n",
|
||
"台阶指数 2.6471\n",
|
||
"\n",
|
||
"南港乙烯项目管理部\n",
|
||
"BMI 4.3333\n",
|
||
"肺活量 3.8667\n",
|
||
"握力 1.0\n",
|
||
"坐位体前屈 2.6154\n",
|
||
"纵跳 1.8\n",
|
||
"俯卧撑 3.0\n",
|
||
"单脚站立 1.3333\n",
|
||
"选择反应时 2.6667\n",
|
||
"台阶指数 2.9\n",
|
||
"\n",
|
||
"党委党校（培训中心）\n",
|
||
"BMI 4.0\n",
|
||
"肺活量 3.6591\n",
|
||
"握力 1.0\n",
|
||
"坐位体前屈 2.975\n",
|
||
"纵跳 1.8182\n",
|
||
"俯卧撑 2.4444\n",
|
||
"一分钟仰卧起坐 3.9333\n",
|
||
"单脚站立 2.4048\n",
|
||
"选择反应时 3.3125\n",
|
||
"台阶指数 2.9444\n",
|
||
"\n",
|
||
"装备研究院\n",
|
||
"BMI 4.2083\n",
|
||
"肺活量 3.6458\n",
|
||
"握力 1.1875\n",
|
||
"坐位体前屈 2.6522\n",
|
||
"纵跳 2.0667\n",
|
||
"俯卧撑 2.28\n",
|
||
"一分钟仰卧起坐 4.5\n",
|
||
"单脚站立 2.1064\n",
|
||
"选择反应时 3.0208\n",
|
||
"台阶指数 2.5385\n",
|
||
"\n",
|
||
"热电部\n",
|
||
"BMI 3.545\n",
|
||
"肺活量 3.297\n",
|
||
"握力 1.457\n",
|
||
"坐位体前屈 2.7988\n",
|
||
"纵跳 2.0687\n",
|
||
"俯卧撑 2.702\n",
|
||
"一分钟仰卧起坐 3.9048\n",
|
||
"单脚站立 2.0026\n",
|
||
"选择反应时 3.0246\n",
|
||
"台阶指数 2.8593\n",
|
||
"\n",
|
||
"烯烃部\n",
|
||
"BMI 3.7003\n",
|
||
"肺活量 3.1226\n",
|
||
"握力 1.3396\n",
|
||
"坐位体前屈 3.043\n",
|
||
"纵跳 1.9135\n",
|
||
"俯卧撑 2.4788\n",
|
||
"一分钟仰卧起坐 3.9538\n",
|
||
"单脚站立 2.0804\n",
|
||
"选择反应时 3.1009\n",
|
||
"台阶指数 2.8376\n",
|
||
"\n",
|
||
"行政事务中心\n",
|
||
"BMI 3.8293\n",
|
||
"肺活量 3.0833\n",
|
||
"握力 1.325\n",
|
||
"坐位体前屈 2.4375\n",
|
||
"纵跳 1.7\n",
|
||
"俯卧撑 3.4211\n",
|
||
"一分钟仰卧起坐 4.2667\n",
|
||
"单脚站立 2.1282\n",
|
||
"选择反应时 2.9512\n",
|
||
"台阶指数 2.6842\n",
|
||
"\n",
|
||
"信息档案管理中心\n",
|
||
"BMI 4.1525\n",
|
||
"肺活量 3.7119\n",
|
||
"握力 1.05\n",
|
||
"坐位体前屈 3.0566\n",
|
||
"纵跳 1.8393\n",
|
||
"俯卧撑 2.92\n",
|
||
"一分钟仰卧起坐 4.0952\n",
|
||
"单脚站立 2.4746\n",
|
||
"选择反应时 3.2034\n",
|
||
"台阶指数 2.8824\n",
|
||
"\n",
|
||
"研究院\n",
|
||
"BMI 4.0099\n",
|
||
"肺活量 3.5306\n",
|
||
"握力 1.3069\n",
|
||
"坐位体前屈 2.8161\n",
|
||
"纵跳 1.9529\n",
|
||
"俯卧撑 3.1481\n",
|
||
"一分钟仰卧起坐 4.1818\n",
|
||
"单脚站立 2.1515\n",
|
||
"选择反应时 3.3366\n",
|
||
"台阶指数 2.975\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"for k ,v in dict3.items():\n",
|
||
" print(k)\n",
|
||
" for k1,v1 in v.items():\n",
|
||
" if v1['count']>0:\n",
|
||
" print(k1,round(v1['score']/v1['count'],4))\n",
|
||
" print()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "2ed551b0-85d5-40d4-8cc1-fd0a0c330ad9",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.10.12"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|