I'm using Pandas and Numpy and I'm trying to replace all NaN values in a Series like this one:
date a
2017-04-24 01:00:00 [1,0,0]
2017-04-24 01:20:00 [1,0,0]
2017-04-24 01:40:00 NaN
2017-04-24 02:00:00 NaN
2017-04-24 02:20:00 [0,1,0]
2017-04-24 02:40:00 [1,0,0]
2017-04-24 03:00:00 NaN
2017-04-24 03:20:00 [0,0,1]
2017-04-24 03:40:00 NaN
2017-04-24 04:00:00 [1,0,0]
with the nearest objcet (a Numpy array in this case). The result is:
date a
2017-04-24 01:00:00 [1,0,0]
2017-04-24 01:20:00 [1,0,0]
2017-04-24 01:40:00 [1,0,0]
2017-04-24 02:00:00 [0,1,0]
2017-04-24 02:20:00 [0,1,0]
2017-04-24 02:40:00 [1,0,0]
2017-04-24 03:00:00 [1,0,0]
2017-04-24 03:20:00 [0,0,1]
2017-04-24 03:40:00 [0,0,1]
2017-04-24 04:00:00 [1,0,0]
Does someone know an efficient method to do it? Many thanks.