173 lines
7.6 KiB
Python
173 lines
7.6 KiB
Python
import openpyxl # 添加缺少的导入
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import json
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import os
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from Config.Config import EXCEL_PATH
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from Util.AreaUtil import query_area_info
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# 创建数据保存目录
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DATA_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'Data')
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os.makedirs(DATA_DIR, exist_ok=True)
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JSON_PATH = os.path.join(DATA_DIR, 'MaoRuXueLv.json') # 修改为毛入学率的JSON路径
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file_name = EXCEL_PATH
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enrollment_data = []
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name_conversion_errors = [] # 记录转换失败的名称
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conversion_records = [] # 定义转换记录变量
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try:
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# 加载工作簿并选择毛入学率Sheet
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workbook = openpyxl.load_workbook(file_name, read_only=True)
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if '毛入学率' not in workbook.sheetnames:
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print("❌ 错误：未找到'毛入学率'Sheet")
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exit(1)
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sheet = workbook['毛入学率']
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# 定义数据列范围与英文属性映射
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# 学前教育（交替列逻辑）
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data_columns = {
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# 学前教育 - 交替列映射（2015-2024）
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'preschool_enrollment': {
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'columns': ['D', 'F', 'H', 'J', 'L', 'N', 'P', 'R', 'T', 'V'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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'preschool_enrollment_rate': {
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'columns': ['E', 'G', 'I', 'K', 'M', 'O', 'Q', 'S', 'U', 'W'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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# 小学教育（X-AQ列，交替列逻辑）
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'primary_enrollment': {
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'columns': ['X', 'Z', 'AB', 'AD', 'AF', 'AH', 'AJ', 'AL', 'AN', 'AP'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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'primary_enrollment_rate': {
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'columns': ['Y', 'AA', 'AC', 'AE', 'AG', 'AI', 'AK', 'AM', 'AO', 'AQ'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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# 初中教育（AR-BK列，交替列逻辑）
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'junior_high_enrollment': {
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'columns': ['AR', 'AT', 'AV', 'AX', 'AZ', 'BB', 'BD', 'BF', 'BH', 'BJ'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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'junior_high_enrollment_rate': {
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'columns': ['AS', 'AU', 'AW', 'AY', 'BA', 'BC', 'BE', 'BG', 'BI', 'BK'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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# 普通高中教育（BL-CE列，交替列逻辑）
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'senior_high_enrollment': {
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'columns': ['BL', 'BN', 'BP', 'BR', 'BT', 'BV', 'BX', 'BZ', 'CB', 'CD'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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'senior_high_enrollment_rate': {
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'columns': ['BM', 'BO', 'BQ', 'BS', 'BU', 'BW', 'BY', 'CA', 'CC', 'CE'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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# 中职教育（CF-CY列，交替列逻辑）
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'vocational_enrollment': {
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'columns': ['CF', 'CH', 'CJ', 'CL', 'CN', 'CP', 'CR', 'CT', 'CV', 'CX'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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},
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'vocational_enrollment_rate': {
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'columns': ['CG', 'CI', 'CK', 'CM', 'CO', 'CQ', 'CS', 'CU', 'CW', 'CY'],
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'years': [2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024]
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}
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}
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# 遍历数据行（跳过前4行表头）
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for row_num, row in enumerate(sheet.iter_rows(min_row=5, values_only=True), start=5):
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# 区域名称从B列获取（索引1），原代码是从A列（索引0）获取
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raw_name = row[1] if (len(row) > 1 and row[1] is not None) else '未知地区'
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if not raw_name: # 跳过空行
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continue
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# 区域名称转换（核心修改）
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# 确保raw_name为字符串类型再调用strip()
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str_raw_name = str(raw_name).strip() if raw_name is not None else '未知地区'
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area_info = query_area_info(str_raw_name)
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if area_info:
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area_name = area_info['full_name']
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area_code = area_info['area_code']
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# 检查是否发生实际转换
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if raw_name != area_name:
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conversion_records.append({
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'row': row_num,
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'raw_name': raw_name,
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'converted_name': area_name
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})
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else:
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area_name = raw_name
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area_code = 'unknown'
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name_conversion_errors.append(f"行 {row_num}: '{raw_name}'")
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area_data = {
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'area_name': area_name,
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'area_code': area_code,
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'raw_name': raw_name # 保留原始名称用于调试
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}
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# 提取各指标年度数据
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for metric, config in data_columns.items():
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year_data = {}
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# 仅保留显式列名映射处理逻辑（完全移除旧格式代码）
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if 'columns' in config and 'years' in config:
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# 遍历预设的列名和年份对应关系
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for col_name, year in zip(config['columns'], config['years']):
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col_idx = openpyxl.utils.column_index_from_string(col_name) - 1
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if col_idx < len(row):
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value = row[col_idx]
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# 处理空值和非数值（增强版）
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if value is None:
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year_data[str(year)] = 0
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else:
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# 统一转换为字符串处理
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str_value = str(value).strip()
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if str_value == '' or str_value == '####':
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year_data[str(year)] = 0
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else:
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try:
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if '%' in str_value:
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# 移除百分号并转换为小数
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year_data[str(year)] = float(str_value.replace('%', ''))
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else:
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year_data[str(year)] = float(str_value) if '.' in str_value else int(str_value)
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except (ValueError, TypeError):
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year_data[str(year)] = 0
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# 删除旧格式的start_col/end_col处理分支
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area_data[metric] = year_data
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enrollment_data.append(area_data)
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workbook.close()
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# 保存为JSON文件
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with open(JSON_PATH, 'w', encoding='utf-8') as f:
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json.dump(enrollment_data, f, ensure_ascii=False, indent=2)
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# 输出转换结果统计
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print(f"✅ 毛入学率数据提取完成，已保存至：{JSON_PATH}")
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print(f"📊 共处理 {len(enrollment_data)} 条地区数据")
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# 输出转换校验结果
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print("\n=== 名称转换记录 ===")
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if conversion_records:
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for record in conversion_records:
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print(f"🔄 行 {record['row']}: {record['raw_name']} → {record['converted_name']}")
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print(f"📊 共检测到 {len(conversion_records)} 项名称转换")
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else:
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print("📝 不存在名称转换的情况")
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if name_conversion_errors:
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print(f"⚠️ 发现 {len(name_conversion_errors)} 个区域名称转换失败：")
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for error in name_conversion_errors:
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print(f" - {error}")
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else:
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print("✅ 所有区域名称均成功转换为全称")
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except FileNotFoundError:
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print(f"🔴 错误：Excel文件 '{file_name}' 不存在")
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except Exception as e:
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print(f"🔴 处理数据时发生错误：{str(e)}")
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