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python - pandas iterrows() 跳过指定的行

问题描述

我在我的代码中运行一个循环，从保存在我计算机上的 Excel 表中提取 SQL 查询，然后执行该查询。每次查询完成运行时，它都会转到下一行并执行此操作，直到没有更多查询为止。但是，我想添加用户可以根据需要跳过某一行的位置（出于运行时目的）。这是我的循环现在的样子：

    selected_rows = ['1', '2', '4', '5']

    for index, row in loop_file.iterrows():
        print('run(): ' + row['Name'])
        query = row['Logic']
        inner_df = pd.read_sql_query(query, conn)
        if inner_df.empty:
            continue
        inner_df['project_id'] = pr_id
        inner_df['logic_name'] = row['Name']
        outer_df = pd.concat([outer_df, inner_df], axis=0, ignore_index=True, sort=False)

    clean_up = 'if object_id ('tempdb..#table') is not null drop table #table'

    cursor.execute(clean_up)

    return outer_df

所以 selected_rows 将是用户从 UI 中选择的行，跳过查询 3。完成我想要做的事情的最有效方法是什么？感谢您的任何指示或提示！

标签： pythonpandasdataframe

解决方案

您可以将selected_rows用作数据框的索引。

像这样：

# this is assumed to be the index
    selected_rows = [1, 2, 4, 5]
# filter to only contain the selected indices
filtered = loop_file[selected_rows]

# proceed as previously
for index, row in filtered.iterrows():
    print('run(): ' + row['Name'])
    query = row['Logic']
    inner_df = pd.read_sql_query(query, conn)
    if inner_df.empty:
        continue
    inner_df['project_id'] = pr_id
    inner_df['logic_name'] = row['Name']
    outer_df = pd.concat([outer_df, inner_df], axis=0, ignore_index=True, sort=False)

clean_up = 'if object_id ('tempdb..#table') is not null drop table #table'

cursor.execute(clean_up)

return outer_df

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