Question

我需要用NA替换数据框的某些列。我可以部分执行此操作，但是列中的某些值不会转换为NA。

这是您可以使用的示例数据框：


df = pd.DataFrame({'away_score': {672: 2.0,
  673: 1.0,
  674: 2.0,
  675: 2.0,
  676: 1.0,
  677: 1.0,
  678: 2.0,
  679: 1.0,
  680: 1.0,
  681: 2.0},
 'home_score': {672: 2.0,
  673: 2.0,
  674: 3.0,
  675: 0.0,
  676: 0.0,
  677: 2.0,
  678: 2.0,
  679: 1.0,
  680: 2.0,
  681: 2.0},
 'match_id': {672: 273236,
  673: 273234,
  674: 273239,
  675: 273231,
  676: 273232,
  677: 273238,
  678: 273237,
  679: 273240,
  680: 273233,
  681: 273235},
 'match_status': {672: 'Finished',
  673: 'Finished',
  674: 'Finished',
  675: 'Finished',
  676: 'Finished',
  677: 'Finished',
  678: 'Finished',
  679: 'Finished',
  680: 'Finished',
  681: 'Finished'}})

到目前为止，我的代码：


columns_to_fillna = ["match_status","home_score","away_score"]

for column in columns_to_fillna:
    df[column] = df[column].apply(lambda row: df[column].replace(row,np.nan))

这以某种方式更改了home_score和away_score列的某些行，并且某些行保持不变。这里可能是什么问题？

Answer 1

>>> columns_to_fillna = ["match_status","home_score","away_score"]

>>> df.replace(df[columns_to_fillna], np.nan)

     away_score  home_score  match_id  match_status
672         NaN         NaN    273236           NaN
673         NaN         NaN    273234           NaN
674         NaN         NaN    273239           NaN
675         NaN         NaN    273231           NaN
676         NaN         NaN    273232           NaN
677         NaN         NaN    273238           NaN
678         NaN         NaN    273237           NaN
679         NaN         NaN    273240           NaN
680         NaN         NaN    273233           NaN
681         NaN         NaN    273235           NaN

用熊猫替换某列的某些值而不是另一些

1 个答案: