What's the difference between a cell value of NaN and None? I used df.dropna(), which drops all NaN but I still have a lot of None.
I am wondering what's the difference between them and how do I get rid of None as well?
Thanks!
What's the difference between a cell value of NaN and None? I used df.dropna(), which drops all NaN but I still have a lot of None.
I am wondering what's the difference between them and how do I get rid of None as well?
Thanks!
@szeitlin already gave a link to a similar question, but if you need this: you can convert a NaN to None
df1 = df.where((pd.notnull(df)), None)
or None to NaN:
import numpy as np
x = np.array(x)
x = x.astype(float)