用混合数据类型删除PANDAS DataFrame中的所有行，这些数据类型包含多个列中的特定字符串

Question

，如果一行包含'9999 dons noce'在任何列中，我如何删除数据框中的所有行？

我已经能够在整个dataFrame中找到基于值（字符串，数值等）的行删除行的解决方案，或者根据特定列中的值删除行，或从具有的dataframe中删除已具有的行几列使用其名称。

这是我发现的最接近的东西，但是这个解决方案对我不起作用，因为由于纯音符（76列以上），我无法输入所有列名。

以下是示例数据集

pd.DataFrame.from_items([('RespondentId', ['1ghi3g','335hduu','4vlsiu4','5nnvkkt','634deds','7kjng']), ('Satisfaction - Timing', ['9-Excellent','9-Excellent','9999-Don't Know','8-Very Good','1-Very Unsatisfied','9999-Don't Know']),('Response Speed - Time',['9999-Don't Know','9999-Don't Know','9-Excellent','9-Excellent','9-Excellent','9-Excellent'])])

删除包含" 9999不知道"的4行后，输出应该看起来像这样，以便我可以用已清理数据编写一个新的Excel文件。

pd.DataFrame.from_items([('RespondentId', ['5nnvkkt','634deds']), ('Satisfaction - Timing', ['8-Very Good','1-Very Unsatisfied']),('Response Speed - Time',['9-Excellent','9-Excellent'])]) 

Answer 1

使用

In [677]: df[~(df == "9999-Don't Know").any(axis=1)]
Out[677]:
  RespondentId Satisfaction - Timing Response Speed - Time
3      5nnvkkt           8-Very Good           9-Excellent
4      634deds    1-Very Unsatisfied           9-Excellent

或

In [683]: df[(df != "9999-Don't Know").all(axis=1)]
Out[683]:
  RespondentId Satisfaction - Timing Response Speed - Time
3      5nnvkkt           8-Very Good           9-Excellent
4      634deds    1-Very Unsatisfied           9-Excellent

与

相同

In [686]: df[~df.eq("9999-Don't Know").any(axis=1)]
Out[686]:
  RespondentId Satisfaction - Timing Response Speed - Time
3      5nnvkkt           8-Very Good           9-Excellent
4      634deds    1-Very Unsatisfied           9-Excellent

或

In [687]: df[df.ne("9999-Don't Know").all(axis=1)]
Out[687]:
  RespondentId Satisfaction - Timing Response Speed - Time
3      5nnvkkt           8-Very Good           9-Excellent
4      634deds    1-Very Unsatisfied           9-Excellent

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使用混合列类型，请参阅 @Pir的评论df.astype(object)

In [695]: df[df.astype(object).ne("9999-Don't Know").all(axis=1)]
Out[695]:
  RespondentId Satisfaction - Timing Response Speed - Time
3      5nnvkkt           8-Very Good           9-Excellent
4      634deds    1-Very Unsatisfied           9-Excellent