20230421
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "9caef37c-26bd-4590-abe6-4c0255c2886f",
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"metadata": {},
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"source": [
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"## 人员基本信息导入"
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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": 2,
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"id": "6ab7bf77-5451-4773-9b13-10e04a48ddfb",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-21T06:44:50.778622Z",
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"iopub.status.busy": "2023-04-21T06:44:50.777794Z",
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"iopub.status.idle": "2023-04-21T06:44:51.048732Z",
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"shell.execute_reply": "2023-04-21T06:44:51.047657Z",
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"shell.execute_reply.started": "2023-04-21T06:44:50.778580Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"ok\n"
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]
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}
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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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"wb = openpyxl.load_workbook('data/高新区名单.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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"for n in range(2, sheet.max_row+1):\n",
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" if sheet.cell(n,2).value is None:\n",
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" break\n",
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" else: \n",
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" code = int(sheet.cell(n, 1).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, 2).value \n",
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" sex = str(sheet.cell(n, 3).value)\n",
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" dict1['sex'] = sex\n",
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" dict1['birth'] = str(sheet.cell(n,8).value).split(' ')[0]\n",
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" if sheet.cell(n,5).value is not None:\n",
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" dict1['phone'] = sheet.cell(n,5).value\n",
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" person[code] = dict1\n",
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"filename = 'data/高新区.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": "502638d8-79d0-4392-953e-047c8428c9a5",
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"metadata": {},
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"source": [
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"## 统计测评人员"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a430da5f-1e5c-447f-96a1-344d03e57b31",
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"metadata": {},
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"source": [
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"### 统计心理测评人员"
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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": 8,
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"id": "7609f3c3-5c52-4b92-a2d5-359bf4a45a10",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-21T07:01:46.516495Z",
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"iopub.status.busy": "2023-04-21T07:01:46.515666Z",
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"iopub.status.idle": "2023-04-21T07:01:46.605645Z",
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"shell.execute_reply": "2023-04-21T07:01:46.604904Z",
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"shell.execute_reply.started": "2023-04-21T07:01:46.516452Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"213\n"
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]
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}
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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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"import csv\n",
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"filename = 'data/高新区.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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"cjry = set()\n",
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"filename = 'data/Survey_20230421-psy.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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" cjry.add(line[2])\n",
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"print(len(cjry))\n",
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"list2 = []\n",
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"for k, v in person.items(): \n",
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" #if 'phone' in v.keys() and v['phone'] in cjry:\n",
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" if 'phone' in v.keys() and v['phone'] not in cjry:\n",
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" list2.append([k,dict1[str(k)]['name'],dict1[str(k)]['phone']])\n",
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" \n",
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"filename = 'data/高新未参加心理评估人员(20230421).xlsx'\n",
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"wb = openpyxl.Workbook()\n",
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"sheet = wb.active\n",
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"#sheet.append(title)\n",
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"for row in list2:\n",
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" sheet.append(row)\n",
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" \n",
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"wb.save(filename)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "519d9b3a-d0d8-44aa-a17d-65e7f21f088b",
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"metadata": {},
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"source": [
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"### 统计中医测评人员"
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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,
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"id": "fd2391c1-8d73-4714-8c20-42161b3eb493",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-21T07:03:35.174975Z",
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"iopub.status.busy": "2023-04-21T07:03:35.174533Z",
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"iopub.status.idle": "2023-04-21T07:03:35.240353Z",
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"shell.execute_reply": "2023-04-21T07:03:35.239435Z",
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"shell.execute_reply.started": "2023-04-21T07:03:35.174944Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"217\n"
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]
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}
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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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"import csv\n",
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"filename = 'data/高新区.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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"cjry = set()\n",
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"filename = 'data/Survey_20230421-tcm1.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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" cjry.add(line[2])\n",
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"print(len(cjry))\n",
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"list2 = []\n",
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"for k, v in person.items(): \n",
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" #if 'phone' in v.keys() and v['phone'] in cjry:\n",
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" if 'phone' in v.keys() and v['phone'] not in cjry:\n",
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" list2.append([k,dict1[str(k)]['name'],dict1[str(k)]['phone']])\n",
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" \n",
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"filename = 'data/高新未参加中医评估人员(20230421).xlsx'\n",
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"wb = openpyxl.Workbook()\n",
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"sheet = wb.active\n",
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"#sheet.append(title)\n",
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"for row in list2:\n",
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" sheet.append(row)\n",
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" \n",
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"wb.save(filename)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0b717a78-52db-4894-83c6-731a4935a02d",
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"metadata": {},
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"source": [
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"### 统计信息缺少人员信息"
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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": 13,
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"id": "fd5af221-9369-4eab-884c-06885c940d88",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2023-04-21T07:16:05.935096Z",
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"iopub.status.busy": "2023-04-21T07:16:05.934235Z",
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"iopub.status.idle": "2023-04-21T07:16:05.967884Z",
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"shell.execute_reply": "2023-04-21T07:16:05.966719Z",
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"shell.execute_reply.started": "2023-04-21T07:16:05.935054Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"235\n"
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]
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}
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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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"import csv\n",
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"filename = 'data/高新区.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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"cjry = set()\n",
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"filename = 'data/Survey_20230421.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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" cjry.add(line[2])\n",
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"print(len(cjry))\n",
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"phones = set()\n",
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"for k, v in person.items(): \n",
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" #if 'phone' in v.keys() and v['phone'] in cjry:\n",
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" if 'phone' in v.keys():\n",
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" phones.add(v['phone'])\n",
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"list2 = []\n",
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"for item in cjry: \n",
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" if item not in phones:\n",
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" list2.append(['','',item])\n",
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"filename = 'data/高新缺失信息人员(20230421).xlsx'\n",
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"wb = openpyxl.Workbook()\n",
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"sheet = wb.active\n",
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"#sheet.append(title)\n",
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"for row in list2:\n",
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" sheet.append(row)\n",
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" \n",
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"wb.save(filename)"
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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": "01933c1f-b7e8-46ff-8a52-f415fca82e27",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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