1788 lines
57 KiB
Plaintext
1788 lines
57 KiB
Plaintext
{
|
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"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e764be85-0ddf-4055-abd6-de2990e75db8",
|
||
"metadata": {
|
||
"tags": [],
|
||
"toc-hr-collapsed": true
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||
},
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||
"source": [
|
||
"# 第一次体测"
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||
]
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ae533fe9-e20e-4e44-b9bb-030c4fa4e714",
|
||
"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",
|
||
"execution_count": 3,
|
||
"id": "1144aaac-92a0-4bcf-aba7-096f7dd3ad3b",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-04-28T08:05:05.494533Z",
|
||
"iopub.status.busy": "2023-04-28T08:05:05.494066Z",
|
||
"iopub.status.idle": "2023-04-28T08:05:06.489698Z",
|
||
"shell.execute_reply": "2023-04-28T08:05:06.488731Z",
|
||
"shell.execute_reply.started": "2023-04-28T08:05:05.494503Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok\n"
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||
]
|
||
}
|
||
],
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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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||
{
|
||
"cell_type": "markdown",
|
||
"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": 9,
|
||
"id": "d5171966-95ae-47ae-a75e-db08de772348",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-04-28T08:30:24.695022Z",
|
||
"iopub.status.busy": "2023-04-28T08:30:24.694269Z",
|
||
"iopub.status.idle": "2023-04-28T08:30:24.860969Z",
|
||
"shell.execute_reply": "2023-04-28T08:30:24.859964Z",
|
||
"shell.execute_reply.started": "2023-04-28T08:30:24.694992Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
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||
"ok\n"
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]
|
||
}
|
||
],
|
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"source": [
|
||
"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",
|
||
"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",
|
||
"print('ok')"
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||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "5e648b69-40bf-4494-9079-e4e2b6ab8866",
|
||
"metadata": {},
|
||
"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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||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "a57ebb22-543c-4804-8d44-89984058ec1d",
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok\n"
|
||
]
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||
}
|
||
],
|
||
"source": [
|
||
"import json\n",
|
||
"import time\n",
|
||
"import csv\n",
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"\n",
|
||
"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",
|
||
"#print(list1)\n",
|
||
"for result in list1:\n",
|
||
" user = str(result[4])\n",
|
||
" m_item = str(result[0]) \n",
|
||
" re_ta.setdefault(user,{}) \n",
|
||
" re_ta[user]['name'] = str(result[6])\n",
|
||
" re_ta[user]['unit'] = str(result[5]) \n",
|
||
" item_name = item[m_item]['name']\n",
|
||
" re_ta[user].setdefault(item_name,{}) \n",
|
||
" score = int(result[1])/item[m_item]['divisor'] \n",
|
||
" re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n",
|
||
" re_ta[user][item_name]['得分'] =result[2]\n",
|
||
"filename = 'data/result_天津.json'\n",
|
||
"with open(filename,'w') as fl:\n",
|
||
" json.dump(re_ta, fl) \n",
|
||
"print('ok')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "55d961e5-a512-44b2-808e-7c55d7000d52",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 导出测试成绩"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "38397ad4-2bb3-4b5e-8ece-9ea11e801890",
|
||
"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",
|
||
"\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():\n",
|
||
" list2 = []\n",
|
||
" list2.append(str(k).rjust(8,'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",
|
||
" \n",
|
||
" for item in items:\n",
|
||
" if item in v.keys():\n",
|
||
" list2.append(v[item]['成绩'])\n",
|
||
" \n",
|
||
" elif item =='name':\n",
|
||
" list2.append(v[item])\n",
|
||
" else:\n",
|
||
" list2.append('') \n",
|
||
" \n",
|
||
" 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",
|
||
"sheet.append(title)\n",
|
||
"for row in list1:\n",
|
||
" sheet.append(row)\n",
|
||
" \n",
|
||
"wb.save(filename)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "239ceb76-f690-4dae-991c-62c38d617c85",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 导出测试成绩(带得分)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "27529013-f3de-4e23-980d-f62203e4df88",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-04-30T01:28:04.696517Z",
|
||
"iopub.status.busy": "2023-04-30T01:28:04.695670Z",
|
||
"iopub.status.idle": "2023-04-30T01:28:06.723602Z",
|
||
"shell.execute_reply": "2023-04-30T01:28:06.722564Z",
|
||
"shell.execute_reply.started": "2023-04-30T01:28:04.696475Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok\n"
|
||
]
|
||
}
|
||
],
|
||
"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",
|
||
"\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"
|
||
]
|
||
},
|
||
{
|
||
"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": 25,
|
||
"id": "83f02525-fd26-41ba-8b6a-c3cd584825e6",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-05-11T05:10:37.412656Z",
|
||
"iopub.status.busy": "2023-05-11T05:10:37.412185Z",
|
||
"iopub.status.idle": "2023-05-11T05:10:37.519354Z",
|
||
"shell.execute_reply": "2023-05-11T05:10:37.518601Z",
|
||
"shell.execute_reply.started": "2023-05-11T05:10:37.412628Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
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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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|
||
"30313733313836360000000000000000 c0eeb8a3cdfa00000000000000000000\n",
|
||
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||
"30313733303835360000000000000000 bafab3a4c1ac00000000000000000000\n",
|
||
"30313733303834380000000000000000 c1f5bdf0bbaa00000000000000000000\n",
|
||
"30313733303833320000000000000000 d5d4d6bec3f100000000000000000000\n",
|
||
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|
||
"30313733313833350000000000000000 d3dad1e0000000000000000000000000\n",
|
||
"30313733323637380000000000000000 b8dfbea7000000000000000000000000\n",
|
||
"30333434303630390000000000000000 c2acbaecc1c100000000000000000000\n",
|
||
"30333436383237350000000000000000 d5c5b2a9d3ee00000000000000000000\n",
|
||
"30333436383335360000000000000000 d6a3b1bec3f700000000000000000000\n",
|
||
"30333436383334310000000000000000 c4c2b1a6c3c000000000000000000000\n",
|
||
"30333436383335350000000000000000 d5d4d4bd000000000000000000000000\n",
|
||
"30333436383334360000000000000000 d4acc0da000000000000000000000000\n",
|
||
"30333436383335340000000000000000 d5d4d3f1bde000000000000000000000\n",
|
||
"30333436383332370000000000000000 cdf5d3bed5e900000000000000000000\n",
|
||
"30333436383234380000000000000000 b6a1d2bb000000000000000000000000\n",
|
||
"30333436383235310000000000000000 baced3a6bfed00000000000000000000\n",
|
||
"30333436383331350000000000000000 d1eec8e3e6cc00000000000000000000\n",
|
||
"30333433363834360000000000000000 cee2bae1000000000000000000000000\n",
|
||
"30333439393435310000000000000000 c1f5c5e0b1f500000000000000000000\n",
|
||
"30333439393430300000000000000000 b7bfbaead3ee00000000000000000000\n",
|
||
"30333439393336370000000000000000 b8dfbac6bae300000000000000000000\n",
|
||
"30333439393437350000000000000000 c1f5cdae000000000000000000000000\n",
|
||
"30333439393432300000000000000000 c7d8d1a7c9ad00000000000000000000\n",
|
||
"30333439393334390000000000000000 c9eab3ac000000000000000000000000\n",
|
||
"30333439393433340000000000000000 b9f9d4aac9fa00000000000000000000\n",
|
||
"30333439393335300000000000000000 c5d3bcd1c0d600000000000000000000\n",
|
||
"30333439393339340000000000000000 cbd5ccda000000000000000000000000\n",
|
||
"30333439393336390000000000000000 c0eeb0c2000000000000000000000000\n",
|
||
"30333530353732340000000000000000 d1eebdf0c5f300000000000000000000\n",
|
||
"30333530353735300000000000000000 b7b6d6bed2e300000000000000000000\n",
|
||
"30333530353733310000000000000000 c0eed4f3b3bf00000000000000000000\n",
|
||
"30333530353731360000000000000000 b3c2bcd1e2f900000000000000000000\n",
|
||
"30333332313739300000000000000000 bfb5b7b2000000000000000000000000\n",
|
||
"ok!\n"
|
||
]
|
||
}
|
||
],
|
||
"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": 183,
|
||
"id": "695b4933-b8c3-4be6-a024-742a982f0abb",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-01-14T08:57:36.572541Z",
|
||
"iopub.status.busy": "2023-01-14T08:57:36.571983Z",
|
||
"iopub.status.idle": "2023-01-14T08:57:36.671348Z",
|
||
"shell.execute_reply": "2023-01-14T08:57:36.670273Z",
|
||
"shell.execute_reply.started": "2023-01-14T08:57:36.572493Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{2: {'男': {'num': 700, 'score': 1913.639999999998, 'zhongyi': 91, 'pianpo': 73}, '女': {'num': 550, 'score': 1736.5499999999988, 'zhongyi': 47, 'pianpo': 43}}, 1: {'男': {'num': 465, 'score': 1291.3899999999994, 'zhongyi': 153, 'pianpo': 119}, '女': {'num': 265, 'score': 846.3700000000005, 'zhongyi': 47, 'pianpo': 45}}, 3: {'男': {'num': 1161, 'score': 3063.0399999999995, 'zhongyi': 144, 'pianpo': 109}, '女': {'num': 279, 'score': 865.81, 'zhongyi': 39, 'pianpo': 34}}, 4: {'男': {'num': 163, 'score': 406.15000000000003, 'zhongyi': 23, 'pianpo': 19}}, 0: {'女': {'num': 405, 'score': 1218.0100000000002, 'zhongyi': 40, 'pianpo': 27}, '男': {'num': 737, 'score': 1971.2600000000007, 'zhongyi': 87, 'pianpo': 44}}, 5: {'男': {'num': 1, 'score': 2.57, 'zhongyi': 0, 'pianpo': 0}}}\n"
|
||
]
|
||
}
|
||
],
|
||
"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": 188,
|
||
"id": "181ff60b-3372-441a-8cd7-29e8de66ceb8",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-01-14T09:14:36.031368Z",
|
||
"iopub.status.busy": "2023-01-14T09:14:36.030813Z",
|
||
"iopub.status.idle": "2023-01-14T09:14:36.136340Z",
|
||
"shell.execute_reply": "2023-01-14T09:14:36.135039Z",
|
||
"shell.execute_reply.started": "2023-01-14T09:14:36.031320Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{2: {'num': 1250, 'score': 3650.189999999998, 'zhongyi': 138, 'pianpo': 116}, 1: {'num': 730, 'score': 2137.7599999999993, 'zhongyi': 200, 'pianpo': 164}, 3: {'num': 1440, 'score': 3928.850000000005, 'zhongyi': 183, 'pianpo': 143}, 4: {'num': 163, 'score': 406.15000000000003, 'zhongyi': 23, 'pianpo': 19}, 0: {'num': 1142, 'score': 3189.270000000001, 'zhongyi': 127, 'pianpo': 71}, 5: {'num': 1, 'score': 2.57, 'zhongyi': 0, 'pianpo': 0}}\n",
|
||
"ok!\n"
|
||
]
|
||
}
|
||
],
|
||
"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": 192,
|
||
"id": "d5ab1a99-cb3e-4905-8c05-a6122ea09913",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-01-14T09:22:28.467869Z",
|
||
"iopub.status.busy": "2023-01-14T09:22:28.467341Z",
|
||
"iopub.status.idle": "2023-01-14T09:22:28.568909Z",
|
||
"shell.execute_reply": "2023-01-14T09:22:28.567550Z",
|
||
"shell.execute_reply.started": "2023-01-14T09:22:28.467822Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok!\n"
|
||
]
|
||
}
|
||
],
|
||
"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": 4,
|
||
"id": "255b5649-fb85-424d-9fad-0f3e1dff2be3",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-02-14T14:30:30.331426Z",
|
||
"iopub.status.busy": "2023-02-14T14:30:30.330830Z",
|
||
"iopub.status.idle": "2023-02-14T14:30:30.441098Z",
|
||
"shell.execute_reply": "2023-02-14T14:30:30.440041Z",
|
||
"shell.execute_reply.started": "2023-02-14T14:30:30.331376Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"{2: {'num': 571, 'score': 1619.279999999999, 'zhongyi': 55, 'pianpo': 44}, 3: {'num': 665, 'score': 1730.73, 'zhongyi': 76, 'pianpo': 62}, 1: {'num': 129, 'score': 358.9600000000001, 'zhongyi': 23, 'pianpo': 19}, 0: {'num': 706, 'score': 1963.300000000001, 'zhongyi': 70, 'pianpo': 32}, 4: {'num': 81, 'score': 194.23999999999992, 'zhongyi': 17, 'pianpo': 14}}\n",
|
||
"ok!\n"
|
||
]
|
||
}
|
||
],
|
||
"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": {},
|
||
"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": 3,
|
||
"id": "25283932-c03a-4a34-a59d-314fc64d8fbd",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2023-09-15T06:05:41.102421Z",
|
||
"iopub.status.busy": "2023-09-15T06:05:41.102217Z",
|
||
"iopub.status.idle": "2023-09-15T06:05:41.790471Z",
|
||
"shell.execute_reply": "2023-09-15T06:05:41.789908Z",
|
||
"shell.execute_reply.started": "2023-09-15T06:05:41.102407Z"
|
||
},
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"ok\n"
|
||
]
|
||
}
|
||
],
|
||
"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": "code",
|
||
"execution_count": null,
|
||
"id": "d84c41f5-6e8e-48f6-822f-fb8bdfb278b1",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"## 体测人员导入"
|
||
]
|
||
}
|
||
],
|
||
"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
|
||
}
|