Pandas missing values : fill with the closest non NaN value
You could use Series.interpolate with method='nearest':
In [11]: s = pd.Series([0, 1, np.nan, np.nan, np.nan, np.nan, 3])In [12]: s.interpolate(method='nearest')Out[12]: 0 0.01 1.02 1.03 1.04 3.05 3.06 3.0dtype: float64In [13]: s = pd.Series([0, 1, np.nan, np.nan, 2, np.nan, np.nan, 3])In [14]: s.interpolate(method='nearest')Out[14]: 0 0.01 1.02 1.03 2.04 2.05 2.06 3.07 3.0dtype: float64