从 pandas 的数据框中删除无限值? [英] dropping infinite values from dataframes in pandas?

问题描述

从熊猫DataFrame中删除nan和inf/-inf值而不重置mode.use_inf_as_null的最快/最简单方法是什么?我希望能够使用dropna的subset和how参数，除了inf值被认为丢失，例如:

what is the quickest/simplest way to drop nan and inf/-inf values from a pandas DataFrame without resetting mode.use_inf_as_null? I'd like to be able to use the subset and how arguments of dropna, except with inf values considered missing, like:

df.dropna(subset=["col1", "col2"], how="all", with_inf=True)

这可能吗?有没有办法告诉dropna在其缺少值的定义中包括inf?

is this possible? Is there a way to tell dropna to include inf in its definition of missing values?

推荐答案

最简单的方法是首先

The simplest way would be to first replace infs to NaN:

df.replace([np.inf, -np.inf], np.nan)

，然后使用 dropna :

and then use the dropna:

df.replace([np.inf, -np.inf], np.nan).dropna(subset=["col1", "col2"], how="all")

例如:

In [11]: df = pd.DataFrame([1, 2, np.inf, -np.inf])

In [12]: df.replace([np.inf, -np.inf], np.nan)
Out[12]:
    0
0   1
1   2
2 NaN
3 NaN

相同的方法适用于Series.

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