Keep finite entries only in Pandas

Question

In Pandas, I can use df.dropna() to drop any NaN entries. Is there anything similar in Pandas to drop non-finite (e.g. Inf) entries?

Possible duplicate of [dropping infinite values from dataframes in pandas?](https://stackoverflow.com/questions/17477979/dropping-infinite-values-from-dataframes-in-pandas) — chepyle, Jun 07 '18 at 21:36

score 27 · Accepted Answer · answered Jul 29 '14 at 12:53

27

You can use:

with pd.option_context('mode.use_inf_as_null', True):
   df = df.dropna()

answered Jul 29 '14 at 12:53

this causes my dataframe to go from 130 rows to 0. The na/inf issue I'm investigating is a column of all blanks, i believe – 3pitt Jan 22 '18 at 16:44
You can specify the axis you wish to drop NaNs over as a parameter to dropna – Ayrton Bourn Mar 21 '21 at 00:48

score 8 · Answer 2 · answered Jun 24 '16 at 00:02

8

df[np.isfinite(df) | np.isnan(df)]

answered Jun 24 '16 at 00:02

rafaelvalle

score 3 · Answer 3 · answered Apr 02 '14 at 00:08

3

You can use .dropna() after a DF[DF==np.inf]=np.nan, (unless you still want to keep the NANs and only drop the infs)

answered Apr 02 '14 at 00:08

CT Zhu

Thanks. Surprisingly `df.drop(df==np.inf)` doesn't work. Any thoughts why? – Josh Apr 02 '14 at 00:19
2

I think, as the docstring goes: `.dropna(self, axis=0, how='any', thresh=None, subset=None)`, `df==np.inf` will get passed as `axis` argument, with should raise an exception. – CT Zhu Apr 02 '14 at 00:25

3 Answers3