如果某行在任何列中包含“9999-不知道”，我如何删除数据框中的所有行？
我已经找到了解决方案，可以根据整个数据框中的值格式(字符串、数字等)删除行，或者根据特定列中的值删除行，或者从具有以下内容的数据框中删除行使用他们的名字的几列。
This是我找到的最接近的东西，但这个解决方案对我不起作用，因为由于体积庞大(超过 76 列)我无法输入所有列名。
下面是一个示例数据集
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-Don't Know”的 4 行后，输出应如下所示，这样我就可以用清理后的数据编写一个新的 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'])])
请您参考如下方法:
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
或者
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
一样
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
或者
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
混合列类型，见@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
