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in Data Science by (17.6k points)

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)

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

1 Answer

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by (41.4k points)

First replace infs to NaN:

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

and then use the dropna:

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

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