Question :
Remove NaN from pandas series
Is there a way to remove a NaN values from a panda series? I have a series that may or may not have some NaN values in it, and I’d like to return a copy of the series with all the NaNs removed.
Answer #1:
>>> s = pd.Series([1,2,3,4,np.NaN,5,np.NaN])
>>> s[~s.isnull()]
0 1
1 2
2 3
3 4
5 5
update or even better approach as @DSM suggested in comments, using pandas.Series.dropna():
>>> s.dropna()
0 1
1 2
2 3
3 4
5 5
Answer #2:
A small usage of np.nan ! = np.nan
s[s==s]
Out[953]:
0 1.0
1 2.0
2 3.0
3 4.0
5 5.0
dtype: float64
More Info
np.nan == np.nan
Out[954]: False
Answer #3:
If you have a pandas serie with NaN, and want to remove it (without loosing index):
serie = serie.dropna()
# create data for example
data = np.array(['g', 'e', 'e', 'k', 's'])
ser = pd.Series(data)
ser.replace('e', np.NAN)
print(ser)
0 g
1 NaN
2 NaN
3 k
4 s
dtype: object
# the code
ser = ser.dropna()
print(ser)
0 g
3 k
4 s
dtype: object
