熊猫的数据行不会掉

Question

背景--如果所有3x条件都满足的话，我正在尝试从熊猫数据栏(exceptions_df)中删除行。

条件-

1. Ownership Audit Note列值包含ignore或Ignore.
2. Entity ID %列值是== Account # %的部分字符串值(该列格式为float64).
3. % Ownership coumn is == 100 )。(该列被格式化为float64)

提取自dataframe -

  % Ownership     Ownership Audit Note       Entity ID %     Account # %  
0 100.00          [ignore] 100% Ownership    0.0000000       0.0000000  
1 100.00          [ignore] 100% Ownership    0.0000000       0.0000000  
2 100.00          [ignore] 100% Ownership    0.0000000       0.0000000  
3 100.00          [ignore] 100% Ownership    0.0000000       0.0000000    
4 100.00          [ignore] 100% Ownership    0.0000000       0.0000000    
5 100.00          [ignore] 100% Ownership    1.0000000       1.0000000  
8 100.00          [ignore] 100% Ownership    0.0000234       0.0000234  
9 100.00          [ignore] 100% Ownership    0.0000000       0.0000000

我的代码-

exceptions_df = exceptions_df[~exceptions_df['Ownership Audit Note'].str.contains('ignore'|'Ignore') & 
                             [~exceptions_df['% Ownership'] == 100] & 
                             [~exceptions_df['Account # %'] == 'Entity ID %']]

问题--我似乎得到了下面的TypeError:，它引用了上面的代码行。我错过什么明显的东西了吗？奇怪的是，如果我只包含第一条条件/第一行代码，那么它就能正常工作了！

TypeError: unsupported operand type(s) for |: 'str' and 'str'

Answer 1

需要删除.contains()中的内部引号。例如，制作了虚拟df。

exceptions_dict = {'% Ownership': {0: 100.0,
  1: 100.0,
  2: 100.0,
  3: 100.0,
  4: 100.0,
  5: 100.0,
  6: 100.0,
  7: 100.0,
  8: 90.0,
  9: 100.0},
 'Ownership Audit Note': {0: '[ignore] 100% Ownership',
  1: '[ignore] 100% Ownership',
  2: '[ignore] 100% Ownership',
  3: '[ignore] 100% Ownership',
  4: '[ignore] 100% Ownership',
  5: '[ignore] 100% Ownership',
  6: '[ignore] 100% Ownership',
  7: '[ignore] 100% Ownership',
  8: 'foo',
  9: 'foo'},
 'Entity ID %': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 1.0,
  6: 2.34e-05,
  7: 0.0,
  8: 1.0,
  9: 1.0},
 'Account # %': {0: 0.0,
  1: 0.0,
  2: 0.0,
  3: 0.0,
  4: 0.0,
  5: 1.0,
  6: 2.34e-05,
  7: 0.0,
  8: 2.0,
  9: 2.0}}

exceptions_df = pd.DataFrame(exceptions_dict)

exceptions_df = exceptions_df[(~(exceptions_df['Ownership Audit Note'].str.contains('ignore|Ignore'))) & 
                                (~(exceptions_df['% Ownership'] == 100.0)) & 
                                (~(exceptions_df['Account # %'] == 'Entity ID %'))]

print(exceptions_df)

    % Ownership Ownership Audit Note    Entity ID % Account # %
8   90.0        foo                     1.0       2.0

Answer 2

使用错误的分区括号。让我们试试

exceptions_df = exceptions_df[(~(exceptions_df['Ownership Audit Note'].str.contains('ignore'|'Ignore'))) & 
                             (~(exceptions_df['% Ownership'] == 100)) & 
                            ( ~(exceptions_df['Account # %'] == 'Entity ID %'))]