用一系列非數字對象中的最接近的值替換NaN？

Question

我使用的是熊貓和numpy的，我試圖取代在這樣一個系列的所有NaN值：

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] 

與最近objcet（一numpy的陣列在這種情況下）。結果是：

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] 

有人知道有效的方法嗎？非常感謝。

Answer 1

下降零點然後填寫回了reindex

df.set_index('date').a.dropna().reindex(df.date, method='nearest').reset_index() 

       date   a 
0 2017-04-24 01:00:00 [1, 0, 0] 
1 2017-04-24 01:20:00 [1, 0, 0] 
2 2017-04-24 01:40:00 [1, 0, 0] 
3 2017-04-24 02:00:00 [0, 1, 0] 
4 2017-04-24 02:20:00 [0, 1, 0] 
5 2017-04-24 02:40:00 [1, 0, 0] 
6 2017-04-24 03:00:00 [0, 0, 1] 
7 2017-04-24 03:20:00 [0, 0, 1] 
8 2017-04-24 03:40:00 [1, 0, 0] 
9 2017-04-24 04:00:00 [1, 0, 0]