Python pandas: how to remove nan and -inf values

Question

I have the following dataframe

           time       X    Y  X_t0     X_tp0  X_t1     X_tp1  X_t2     X_tp2
0         0.002876    0   10     0       NaN   Na         


        

Answer 1

You can replace inf and -inf with NaN, and then select non-null rows.

df[df.replace([np.inf, -np.inf], np.nan).notnull().all(axis=1)]  # .astype(np.float64) ?

or

df.replace([np.inf, -np.inf], np.nan).dropna(axis=1)

Check the type of your columns returns to make sure they are all as expected (e.g. np.float32/64) via df.info().