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import pandas as pd
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import os
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from datetime import datetime, timedelta
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def get_departure_destination(file_name):
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name_without_extension = os.path.splitext(file_name)[0]
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return name_without_extension
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def merge_csv_files(csv_files, output_xlsx):
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all_dfs = []
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for csv_file in csv_files:
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df = pd.read_csv(csv_file)
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# 添加日期列
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date = os.path.basename(os.path.dirname(os.path.dirname(csv_file)))
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df['出发日期'] = date
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# 选择指定的列
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selected_columns = [
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'航班号','出发城市','到达城市', '航空公司', '出发日期', '出发时间', '到达时间',
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'中转信息', 'economy_origin', '经济舱餐食信息', '经济舱座椅间距', '出发延误时间'
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]
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df = df[selected_columns]
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# 重命名 'economy_origin' 为 '票价'
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df = df.rename(columns={'economy_origin': '票价'})
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all_dfs.append(df)
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# 合并所有数据框
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merged_df = pd.concat(all_dfs, ignore_index=True)
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# 保存为Excel文件
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merged_df.to_excel(output_xlsx, index=False, engine='openpyxl')
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# 设置日期范围
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start_date = datetime(2024, 11, 12)# 起始日期
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end_date = datetime(2024, 11, 19)# 结束日期
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clawer_date = datetime(2024, 11, 12)# 爬虫日期
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# 设置输入和输出文件夹路径
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input_base_path = "./"
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output_folder = "./xlsx_output"
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# 确保输出文件夹存在
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if not os.path.exists(output_folder):
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os.makedirs(output_folder)
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# 用于存储同一始发地和目的地的CSV文件
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route_files = {}
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current_date = start_date
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while current_date <= end_date:
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folder_name = current_date.strftime("%Y-%m-%d")
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folder_path = os.path.join(input_base_path, folder_name, clawer_date.strftime("%Y-%m-%d"))
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if os.path.exists(folder_path):
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for file_name in os.listdir(folder_path):
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if file_name.endswith('.csv'):
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csv_path = os.path.join(folder_path, file_name)
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route = get_departure_destination(file_name)
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if route not in route_files:
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route_files[route] = []
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route_files[route].append(csv_path)
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current_date += timedelta(days=1)
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# 合并并保存每个路线的文件
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for route, files in route_files.items():
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output_xlsx = os.path.join(output_folder, f"{route}.xlsx")
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merge_csv_files(files, output_xlsx)
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print(f"已合并并保存路线: {route} -> {output_xlsx}")
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print("所有CSV文件已成功合并为XLSX文件，并筛选了指定的列")
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