Pandas 不同索引的前向和后向填充

Question

我有以下数据框 df:

             length       timestamp       width
name                                          
testschip-1     NaN 2019-08-01 00:00:00    NaN
testschip-1     NaN 2019-08-01 00:00:09    NaN
testschip-1     2   2019-08-01 00:00:20    NaN
testschip-1     2   2019-08-01 00:00:27    NaN
testschip-1     NaN 2019-08-01 00:00:38    1
testschip-2     4   2019-08-01 00:00:39    2
testschip-2     4   2019-08-01 00:00:57    NaN
testschip-2     4   2019-08-01 00:00:58    NaN
testschip-2     NaN 2019-08-01 00:01:17    NaN
testschip-3     NaN 2019-08-01 00:02:27    NaN
testschip-3     NaN 2019-08-01 00:03:47    NaN

首先，我想从索引 "name" 中删除字符串 "testschip-"，这样我就只能在索引上得到整数。其次，对于每个唯一索引，我想在 'length' 和 'width' 两列上应用前向填充或后向填充（无论是否需要获得 NaN）。每个唯一索引都有相同的 "length" 和 "width"。在 "testschip-3" 上，我不想应用向后或向前填充。如果我对 "testschip-1" 进行反向填充（需要将前两个索引设置为两个“2”），我会在索引 "testschip-1" 的最后一行得到不需要的“4”。我无法预先判断是否必须预先应用向后填充或向前填充，因为我有 400 万行数据开始。

Answer 1

使用：

df.index = df.index.str.lstrip('testschip-').astype(int)
#alternative
#df.index = df.index.str[10:].astype(int)
#df.index = df.index.str.split('-').str[-1].astype(int)
df.groupby(level = 0).apply(lambda x: x.bfill().ffill())

输出

      length           timestamp  width
name                                   
1        2.0 2019-08-01 00:00:00    1.0
1        2.0 2019-08-01 00:00:09    1.0
1        2.0 2019-08-01 00:00:20    1.0
1        2.0 2019-08-01 00:00:27    1.0
1        2.0 2019-08-01 00:00:38    1.0
2        4.0 2019-08-01 00:00:39    2.0
2        4.0 2019-08-01 00:00:57    2.0
2        4.0 2019-08-01 00:00:58    2.0
2        4.0 2019-08-01 00:01:17    2.0
3        NaN 2019-08-01 00:02:27    NaN
3        NaN 2019-08-01 00:03:47    NaN

Pandas 不同索引的前向和后向填充

Pandas forward and backward fill on distinct indices

fill

python-3.x

pandas