从 pandas 中排除列where() [英] Exclude columns from pandas where()

问题描述

我有以下熊猫df:

import pandas as pd
import numpy as np    

pd_df = pd.DataFrame({'Qu1': ['apple', 'potato', 'cheese', 'banana', 'cheese', 'banana', 'cheese', 'potato', 'egg'],
              'Qu2': ['sausage', 'banana', 'apple', 'apple', 'apple', np.nan, 'banana', 'banana', 'banana'],
              'Qu3': ['apple', 'potato', 'sausage', 'cheese', 'cheese', 'potato', 'cheese', 'potato', 'egg']})

我只想在Qu1和Qu2的两列上实现where()，并保留其余部分 原始stackoverflow问题 ，所以我创建了pd1

I'd like to implement where() on two columns only Qu1 and Qu2 and keep the rest original stackoverflow question , so I created pd1

pd1 = pd_df.where(pd_df.apply(lambda x: x.map(x.value_counts()))>=2,
                              "other")[['Qu1', 'Qu2']]

然后我将pd_df，pd_df['Qu3']的其余部分添加到pd1

Then I added a rest of pd_df,pd_df['Qu3'] to pd1

pd1['Qu3'] = pd_df['Qu3']
pd_df = []

我的问题是:最初我想在df的一部分上执行where()并保持其余列不变，所以上面的代码对于大型数据集可能会很危险吗?我可以这样破坏原始数据吗?如果是，最好的方法是什么?

My question is : Originally I want to execute where() on part of df and keep rest of columns as is, so could the code above be dangerous for large dataset ? Can I harm the original data this way ? If yes what the best way to do it ?

非常感谢！

推荐答案

您可以显式地提取原始df的copy，然后覆盖所选的df:

You could just explicitly take a copy of the orig df and then overwrite on a selection of that df:

In [40]:
pd1 = pd_df.copy()
pd1[['Qu1', 'Qu2']] = pd1[['Qu1', 'Qu2']].where(pd_df.apply(lambda x: x.map(x.value_counts()))>=2,
                              "other")
pd1

Out[40]:
      Qu1     Qu2      Qu3
0   other   other    apple
1  potato  banana   potato
2  cheese   apple  sausage
3  banana   apple   cheese
4  cheese   apple   cheese
5  banana   other   potato
6  cheese  banana   cheese
7  potato  banana   potato
8   other  banana      egg

所以这里的区别是我们只对df的一部分进行操作，而不是对整个df进行操作，然后选择感兴趣的cols

So the difference here is that we only operate on a section of the df, rather than the whole df and then select the cols of interest

更新

如果您只想覆盖这些列，则只需选择这些列即可:

If you want to just overwrite those cols then just select those:

In [48]:
pd_df[['Qu1', 'Qu2']] = pd_df[['Qu1', 'Qu2']].where(pd_df.apply(lambda x: x.map(x.value_counts()))>=2,
                              "other")
pd_df

Out[48]:
      Qu1     Qu2      Qu3
0   other   other    apple
1  potato  banana   potato
2  cheese   apple  sausage
3  banana   apple   cheese
4  cheese   apple   cheese
5  banana   other   potato
6  cheese  banana   cheese
7  potato  banana   potato
8   other  banana      egg

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