Pandas：如何过滤掉列中列表中包含字符串模式的行？答案

【问题标题】：Pandas: how to filter out rows containing a string pattern within a list in a column?Pandas：如何过滤掉列中列表中包含字符串模式的行？
【发布时间】：2022-11-02 16:55:07
【问题描述】：

我有一个类似于以下内容的数据框：

df = pd.DataFrame({
    'employee_id' : [123, 456, 789],
    'country_code' : ['US', 'CAN', 'MEX'],
    'comments' : (['good performer', 'due for raise', 'should be promoted'],
                 ['bad performer', 'should be fired', 'speak to HR'],
                 ['recently hired', 'needs training', 'shows promise'])
})

df

    employee_id   country_code   comments
0   123           US             [good performer, due for raise, should be promoted]
1   456           CAN            [bad performer, should be fired, speak to HR]
2   789           MEX            [recently hired, needs training, shows promise]

我希望能够将comments 列过滤为删除任何行包含字符串'performer'。为此，我正在使用：

df = df[~df['comments'].str.contains('performer')]

但是，这会返回一个错误：

TypeError: ufunc 'invert' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

提前感谢您提供的任何帮助！

【问题讨论】：

标签： pandas

【解决方案1】：

如果 IIUC 您需要将 cmets 列分解为字符串而不是列表

df = pd.DataFrame({
    'employee_id' : [123, 456, 789],
    'country_code' : ['US', 'CAN', 'MEX'],
    'comments' : (['good performer', 'due for raise', 'should be promoted'],
                 ['bad performer', 'should be fired', 'speak to HR'],
                 ['recently hired', 'needs training', 'shows promise'])
})
df['comments'] = df['comments'].apply(lambda x : ' '.join(x))
df = df[~df['comments'].str.contains('performer')]
df

【讨论】：

【解决方案2】：

由于您的系列中有列表，因此您无法进行矢量化。您可以使用列表推导：

df2 = df[[all('performer' not in x for x in l)
          for l in df['comments']]]

输出：

   employee_id country_code                                         comments
2          789          MEX  [recently hired, needs training, shows promise]

【讨论】：

【解决方案3】：

df = df[~df['comments'].map(' '.join).str.contains('performer')]

【讨论】：