使用filter函数和for循环过滤多个数据帧

Question

我有多个数据帧，我想对每个数据帧进行过滤，以便每个df只保留由单词“total”组成的列。我有以下for循环，但其效果与我手动执行时不同[aka y15=y15.filter（like='totall'）]

pit_dfs = [y15,y16,y17]

for i in pit_dfs:
    i = i.filter(like='Overall')

可复制示例：

y15 = pd.DataFrame({'Col1-Overall': ['a','b','c','d'],
              'Col2': ['a','b','c','d'],
              'Col3': ['a','b','c','d'],
              'Col4': ['a','b','c','d']})

y16 = pd.DataFrame({'Col1-Overall': ['a','b','c','d'],
              'Col2': ['a','b','c','d'],
              'Col3': ['a','b','c','d'],
              'Col4': ['a','b','c','d']})

y17 = pd.DataFrame({'Col1-Overall': ['a','b','c','d'],
              'Col2': ['a','b','c','d'],
              'Col3': ['a','b','c','d'],
              'Col4': ['a','b','c','d']})

预期产出：

y15
+--------------+
| Col1-Overall |
+--------------+
| a            |
+--------------+
| b            |
+--------------+
| c            |
+--------------+
| d            |
+--------------+

y16
+--------------+
| Col1-Overall |
+--------------+
| a            |
+--------------+
| b            |
+--------------+
| c            |
+--------------+
| d            |
+--------------+

y17
+--------------+
| Col1-Overall |
+--------------+
| a            |
+--------------+
| b            |
+--------------+
| c            |
+--------------+
| d            |
+--------------+

我知道这是一个简单的例子，但在过去的一个小时里，我一直在查看堆栈，没有找到类似的例子。我错过了什么？谢谢

Answer 1

请参见this answer和this example关于Python for循环。循环中的变量是而不是指针，因此您不会更改实际的数据帧

您可以这样做（我还没有测试）：

pit_dfs = [y15,y16,y17,y18,y19]

for idx in range(len(pit_dfs)):
    pit_dfs[idx] = pit_dfs[idx].filter(like='Overall')

Answer 2

这里有一个替代方案：

pit_dfs = [y15,y16,y17,y18,y19]

def filter_cols_like(df, like):
    cols_not_like = [col for col in df.columns if like not in col]
    df.drop(columns=cols_not_like,inplace=True)

for i in pit_dfs:
    filter_cols_like(i,like='Overall')