Say we have a pandas series with the following values
[np.nan, np.nan, 1, np.nan, 2, np.nan]
What is the most efficient way fill the nan value with 0 in the middle. so we have
[np.nan, np.nan, 1, 0, 2, np.nan]
In other word, how to we do interpolation with a fixed value, or a .fillna operation but ignore the nan at the beginning and end of the array.
Current solution, I am using
def interpolate_with_fixed(s, value=0):
i = s.first_valid_index()
j = s.last_valid_index()
s.loc[i:j].fillna(value, inplace=True)
return s
I think your solution is quite idiomatic. Here is an alternative solution:
In [355]: s.loc[s.notnull().idxmax() : s[::-1].notnull().idxmax()].fillna(0, inplace=True)
In [356]: s
Out[356]:
0 NaN
1 NaN
2 1.0
3 0.0
4 2.0
5 NaN
dtype: float64
