70 lines
2.6 KiB
Python
70 lines
2.6 KiB
Python
import pandas as pd
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# 读取Excel文件
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file_path = "/home/baol/tools/数据草稿-案款.xls" # 替换为你的Excel文件路径
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# 读取“账户收”工作表，只保留指定列
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sheet_account_receipt = pd.read_excel(file_path, sheet_name="账户收")
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sheet_account_receipt = sheet_account_receipt[
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["归属本案金额", "到账金额", "到账日期", "缴款人", "案号"]
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]
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# 读取“收入”工作表，表头从第二行开始，只保留指定列
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sheet_income = pd.read_excel(file_path, sheet_name="收入", header=1)
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sheet_income = sheet_income[["对方户名", "交易时间", "金额"]]
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# 统一日期格式
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sheet_account_receipt["到账日期"] = pd.to_datetime(
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sheet_account_receipt["到账日期"]
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).dt.strftime("%Y-%m-%d")
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sheet_income["交易时间"] = pd.to_datetime(sheet_income["交易时间"]).dt.strftime(
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"%Y-%m-%d"
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)
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# 重命名列以便于合并
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sheet_account_receipt.rename(
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columns={"到账金额": "金额", "到账日期": "交易时间"}, inplace=True
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)
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# 合并两个数据框
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merged_df = pd.merge(
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sheet_account_receipt, sheet_income, on=["金额", "交易时间"], how="inner"
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)
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# 排除在某一天同时有多笔金额相同的记录
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filtered_df = merged_df.groupby(["金额", "交易时间"]).filter(lambda x: len(x) == 1)
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# 检索出在某一天同时有多笔金额相同的记录
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duplicate_records = merged_df.groupby(["金额", "交易时间"]).filter(lambda x: len(x) > 1)
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# 将结果保存为新的Excel文件
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output_file_path_filtered = "/home/baol/tools/matched_records.xlsx" # 匹配结果
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output_file_path_duplicates = "/home/baol/tools/duplicate_records.xlsx" # 重复记录
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filtered_df.to_excel(output_file_path_filtered, index=False, engine="openpyxl")
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duplicate_records.to_excel(output_file_path_duplicates, index=False, engine="openpyxl")
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print(f"匹配结果已保存到 {output_file_path_filtered}")
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print(f"重复记录已保存到 {output_file_path_duplicates}")
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# 合并两个数据框，并标记匹配情况
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out_merged_df = pd.merge(
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sheet_account_receipt,
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sheet_income,
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on=['金额', '交易时间'],
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how='outer', # 使用外连接以保留未匹配的记录
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indicator=True # 标记匹配情况
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)
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# 筛选出未匹配的记录
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unmatched_records = out_merged_df[out_merged_df['_merge'] != 'both']
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# 删除用于标记匹配情况的列
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unmatched_records.drop(columns=['_merge'], inplace=True)
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# 将结果保存为新的Excel文件
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output_file_path_unmatched = '/home/baol/tools/unmatched_records.xlsx' # 未匹配记录
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unmatched_records.to_excel(output_file_path_unmatched, index=False, engine='openpyxl')
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print(f"未匹配的所有记录已保存到 {output_file_path_unmatched}") |