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Pandas数据帧行不会下降

string pandas python

William · 技术社区 · 3 年前

背景- 我正在尝试从pandas数据帧中删除行( exceptions_df )如果所有3x条件都满足。

条件-

Ownership Audit Note 列值包含的部分字符串值为 ignore 或 Ignore 。
Entity ID % 列值为== Account # % (此列的格式为 float64 )。
% Ownership coumn是== 100 。(此列的格式为 float64 )

从数据帧中提取-

  % 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- 我似乎得到了以下信息 TypeError: ,它引用了上面的代码行。我错过了什么显而易见的东西吗?奇怪的是,如果我只包含第一个条件/第一行代码,那么它就可以正常工作!

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

1 回复 | 直到 3 年前

Matthew Borish 3 年前

需要删除.contains()中的内引号。例如,Made dummy 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

wwnde 3 年前

使用了错误的分区括号。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 %'))]