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@@ -21,7 +21,7 @@ def column_letter_to_index(col_letter):
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"""将Excel列字母转换为0基索引"""
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return sum((ord(c) - ord('A') + 1) * (26 ** i) for i, c in enumerate(reversed(col_letter.upper()))) - 1
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-def process_csv(df, columns, use_letters, processor):
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+def process_csv(df, columns, use_letters, processor, start_row=0):
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"""处理CSV数据框中的指定列"""
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# 获取要处理的列的索引
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if use_letters: # 如果使用列字母
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@@ -30,7 +30,7 @@ def process_csv(df, columns, use_letters, processor):
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indices = [int(col) for col in columns]
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# 遍历每一行并处理
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- for i in range(len(df)):
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+ for i in range(start_row, len(df)):
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row = df.iloc[i].tolist()
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processed_row = process_row(row, indices, processor)
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df.iloc[i] = processed_row
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@@ -45,10 +45,10 @@ def read_and_process_csv(input_file, output_file, need_search_url_columns, asin_
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df = pd.read_csv(input_file, encoding='cp936', keep_default_na=False)
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# 处理需要添加搜索链接的列
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- process_csv(df, need_search_url_columns, use_letters, lambda value: create_hyperlink(value, base_url))
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+ process_csv(df, need_search_url_columns, use_letters, lambda value: create_hyperlink(value, base_url), start_row)
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# 处理ASIN列
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- process_csv(df, asin_columns, use_letters, create_asin_link)
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+ process_csv(df, asin_columns, use_letters, create_asin_link, start_row + 1)
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# 将处理后的数据写入新的CSV文件
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df.to_csv(output_file, index=False, encoding='utf-8')
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