{ "cells": [ { "cell_type": "markdown", "id": "61f4a6eb-797e-4fe2-95df-e27b316c95f1", "metadata": {}, "source": [ "### 人员基本信息导入" ] }, { "cell_type": "code", "execution_count": 22, "id": "f6bc68b5-9ed8-4b28-ab1a-452107b6429a", "metadata": { "execution": { "iopub.execute_input": "2022-10-26T11:58:59.214911Z", "iopub.status.busy": "2022-10-26T11:58:59.214385Z", "iopub.status.idle": "2022-10-26T11:59:00.200796Z", "shell.execute_reply": "2022-10-26T11:59:00.199708Z", "shell.execute_reply.started": "2022-10-26T11:58:59.214863Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok\n" ] } ], "source": [ "import openpyxl\n", "import json\n", "\n", "wb = openpyxl.load_workbook('data/北海石化监测花名册2022 .xlsx')\n", "sheet = wb.active\n", "# sheets = wb.sheetnames\n", "person = {}\n", "for n in range(2, sheet.max_row+1):\n", " if sheet.cell(n,2).value is None:\n", " break\n", " else: \n", " code = int(sheet.cell(n, 4).value)\n", " person.setdefault(code, {})\n", " dict1 = {}\n", " dict1['name'] = sheet.cell(n, 6).value \n", " xb = str(sheet.cell(n, 7).value)\n", " if xb == '1':\n", " sex = '男'\n", " elif xb =='2':\n", " sex = '女'\n", " dict1['sex'] = sex\n", " dict1['unit'] = sheet.cell(n, 3).value\n", " dict1['birth'] = str(sheet.cell(n,8).value).split(' ')[0]\n", " person[code] = dict1\n", "filename = 'data/北海炼化人员_2022.json'\n", "with open(filename, 'w') as fl:\n", " json.dump(person, fl, ensure_ascii=False)\n", "print('ok')" ] }, { "cell_type": "markdown", "id": "fe54b0b2-0abd-4ee9-827d-0e3a4c9bd1f2", "metadata": {}, "source": [ "### 获取人员测试成绩" ] }, { "cell_type": "code", "execution_count": 29, "id": "97031317-76ed-4404-b922-6ca749e4fd2a", "metadata": { "execution": { "iopub.execute_input": "2022-10-26T15:13:05.551848Z", "iopub.status.busy": "2022-10-26T15:13:05.551291Z", "iopub.status.idle": "2022-10-26T15:13:05.733924Z", "shell.execute_reply": "2022-10-26T15:13:05.732766Z", "shell.execute_reply.started": "2022-10-26T15:13:05.551800Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok\n" ] } ], "source": [ "import json\n", "import time\n", "import csv\n", "\n", "filename = '../item.json'\n", "item = {}\n", "unit = {}\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl) \n", "for k,v in dict1.items():\n", " item[k] = v\n", "#SQL语句为:\n", "# SELECT a.item_id,a.performance,a.score,a.date AS DATE1,a.avatar_id,b.unit,b.name FROM places_result AS a,_zgshhgxs AS b WHERE a.place_id=135 AND a.avatar_id=b.id AND a.avatar_id < 4999\n", "\n", "re_ta = {}\n", "dict1 = {}\n", "list1 = []\n", "#print(\"\\n运动项目信息:\")\n", "filename = 'data/138_2210.csv'\n", "with open(filename,'r',newline='') as csv_file:\n", " fl = csv.reader(csv_file,delimiter=',')\n", " header = next(fl) \n", " for line in fl:\n", " #line = re.sub('[\\r\\n\\f ]{1,}', '', line)\n", " list1.append(line)\n", "#print(list1)\n", "for result in list1:\n", " user = str(result[4])\n", " m_item = str(result[0]) \n", " re_ta.setdefault(user,{}) \n", " re_ta[user]['name'] = str(result[6])\n", " re_ta[user]['unit'] = str(result[5]) \n", " item_name = item[m_item]['name']\n", " re_ta[user].setdefault(item_name,{}) \n", " score = int(result[1])/item[m_item]['divisor'] \n", " re_ta[user][item_name]['成绩'] = f'{score} {item[m_item][\"unit\"]}'\n", " re_ta[user][item_name]['得分'] =result[2]\n", "filename = 'data/result_北海炼化2022.json'\n", "with open(filename,'w') as fl:\n", " json.dump(re_ta, fl) \n", "print('ok')" ] }, { "cell_type": "markdown", "id": "be6b6709-a2b0-4c34-aca1-000e1fb45953", "metadata": {}, "source": [ "### 导出测试成绩" ] }, { "cell_type": "code", "execution_count": 30, "id": "f70a02f2-934e-43ed-93ff-b34cb732dfc6", "metadata": { "execution": { "iopub.execute_input": "2022-10-26T15:13:15.553588Z", "iopub.status.busy": "2022-10-26T15:13:15.553050Z", "iopub.status.idle": "2022-10-26T15:13:15.663507Z", "shell.execute_reply": "2022-10-26T15:13:15.662380Z", "shell.execute_reply.started": "2022-10-26T15:13:15.553540Z" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "items = ['身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "title = ['编号','姓名','性别','单位/部门','身高','体重','肺活量','握力','坐位体前屈','纵跳','俯卧撑','一分钟仰卧起坐','单脚站立','选择反应时','台阶指数']\n", "filename = 'data/result_北海炼化2022.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/北海炼化人员_2022.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", " \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/北海炼化体测情况表(截至20221026).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": "5ec595eb-f979-425e-b7eb-9af094ffb43d", "metadata": {}, "source": [ "### 导入2021年人员信息" ] }, { "cell_type": "code", "execution_count": 23, "id": "a9460ee7-1f60-4a3b-a45d-8a1dba04b920", "metadata": { "execution": { "iopub.execute_input": "2022-10-26T11:59:11.407159Z", "iopub.status.busy": "2022-10-26T11:59:11.406624Z", "iopub.status.idle": "2022-10-26T11:59:11.664219Z", "shell.execute_reply": "2022-10-26T11:59:11.663061Z", "shell.execute_reply.started": "2022-10-26T11:59:11.407111Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "ok\n" ] } ], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'data/北海炼化人员_2022.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "filename = 'data/all_result.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "dict3 = {}\n", "dict3 = dict2['北海炼化']\n", "\n", "for k, v in dict1.items():\n", " name = v['name']\n", " birth = v['birth']\n", " for k1, v1 in dict3.items():\n", " if v1['name'] == name and v1['birth'] == birth:\n", " dict1[k]['old_code'] = int(k1)\n", " dict1[k]['record'] = v1['record']\n", " \n", "filename = 'data/北海炼化人员_2022.json'\n", "with open(filename,'w') as fl:\n", " json.dump(dict1, fl) \n", "print('ok')" ] }, { "cell_type": "markdown", "id": "0a221ef2-0d86-45a7-916e-bce634a57bfe", "metadata": {}, "source": [ "### 核对2021体测人员" ] }, { "cell_type": "code", "execution_count": 24, "id": "61fbd157-f4f0-4c85-98dc-0e79ee99280b", "metadata": { "execution": { "iopub.execute_input": "2022-10-26T11:59:14.395184Z", "iopub.status.busy": "2022-10-26T11:59:14.394650Z", "iopub.status.idle": "2022-10-26T11:59:14.567363Z", "shell.execute_reply": "2022-10-26T11:59:14.566447Z", "shell.execute_reply.started": "2022-10-26T11:59:14.395136Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "00068 张利雄 1987-09-24\n", "00120 黎秀珍 1966-12-22\n", "00259 彭秋丽 1989-08-15\n", "00348 黄宏州 1995-02-19\n", "00424 易华锋 1985-12-02\n", "00524 周爱娟 1971-10-11\n", "00525 马遥碧 1971-06-13\n", "00534 潘永远 1962-03-24\n", "00614 刘文涛 1997-07-13\n", "00689 陈雪 1966-11-14\n", "00725 冯剑秋 1972-01-07\n", "00727 汪纯燕 1971-12-06\n", "00733 曾媛 1972-07-14\n", "00758 谭志坚 1972-04-02\n", "00798 冯鸥 1992-11-24\n" ] } ], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'data/北海炼化人员_2022.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "list1 = []\n", "for k,v in dict1.items():\n", " if 'old_code' in v.keys():\n", " list1.append(v['old_code'])\n", "filename = 'data/all_result.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "dict3 = {}\n", "dict3 = dict2['北海炼化']\n", "for k, v in dict3.items():\n", " if int(k) not in list1:\n", " print(k,v['name'],v['birth'])" ] }, { "cell_type": "markdown", "id": "e6698931-04fb-4dd8-a844-55790cbe3eb9", "metadata": {}, "source": [ "### 比照人员两年成绩" ] }, { "cell_type": "markdown", "id": "727be8d7-8a4c-4cf4-8139-476f407a31b0", "metadata": {}, "source": [ "#### 比照两年单项成绩" ] }, { "cell_type": "code", "execution_count": 28, "id": "d3ca4d45-6a83-4d50-8419-cf8aa9b3aa4c", "metadata": { "execution": { "iopub.execute_input": "2022-10-26T12:11:23.788353Z", "iopub.status.busy": "2022-10-26T12:11:23.787816Z", "iopub.status.idle": "2022-10-26T12:11:23.836530Z", "shell.execute_reply": "2022-10-26T12:11:23.835397Z", "shell.execute_reply.started": "2022-10-26T12:11:23.788303Z" }, "tags": [] }, "outputs": [], "source": [ "import json\n", "import openpyxl\n", "\n", "filename = 'data/北海炼化人员_2022.json'\n", "with open(filename,'r') as fl:\n", " dict1 = json.load(fl)\n", "\n", "list1 = dict1.keys()\n", "items = ['台阶指数']\n", "title = ['编号','姓名','部门','22年台阶指数','21年台阶指数']\n", "filename = 'data/result_北海炼化2022.json'\n", "with open(filename,'r') as fl:\n", " dict2 = json.load(fl)\n", "list4 = []\n", "for k, v in dict2.items():\n", " if k in list1:\n", " list2 = [k,v['name'],v['unit']]\n", " list3 = []\n", " for item in items:\n", " # 获取2022年成绩\n", " if item in v.keys(): \n", " list2.append(v[item]['成绩'].split()[0]) \n", " else:\n", " list2.append('')\n", " # 获取2021年成绩\n", " if 'record' in dict1[k].keys() and item in dict1[k]['record'].keys():\n", " list3.append(dict1[k]['record'][item]['成绩']) \n", " else:\n", " list3.append('')\n", " for cj in list3:\n", " if cj != '':\n", " list2.append(cj.split()[0]) \n", " \n", " list4.append(list2)\n", "filename = 'data/b北海炼化成绩对照221026.xlsx'\n", "wb = openpyxl.Workbook()\n", "sheet = wb.active\n", "sheet.append(title)\n", "for row in list4:\n", " sheet.append(row)\n", " \n", "wb.save(filename) " ] }, { "cell_type": "code", "execution_count": null, "id": "70de1be8-e55c-4b7a-bad9-78ad77f199d0", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }