本文介绍了按时间序列向后替换NA仅限于数量有限的观测值的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
在数据表中，我想在两个方向上进行为期3天的向前和向后的间隙填充过程.
In a data table I want to perform a forward and backward gap-filling procedure over a period of 3 days in both directions.
# Example data:
library(data.table)
library(zoo)
dt <- data.table(Value = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.1359223, NA, NA, NA, NA, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, NA))
> dt
Value
1: NA
2: NA
3: NA
4: NA
5: NA
6: NA
7: NA
8: NA
9: NA
10: 0.1359223
11: NA
12: NA
13: NA
14: NA
15: 0.0000000
16: 0.0000000
17: 0.0000000
18: 0.0000000
19: 0.0000000
20: NA
因此，我想创建两列新列，一列用NA向前替换，另一列用向后替换.
Therefore I want to create two new columns, one with forward replacement of the NAs and one with the backward replacement.
# desired output
Value forward backward
1: NA NA NA
2: NA NA NA
3: NA NA NA
4: NA NA NA
5: NA NA NA
6: NA NA NA
7: NA NA 0.1359223
8: NA NA 0.1359223
9: NA NA 0.1359223
10: 0.1359223 0.1359223 0.1359223
11: NA 0.1359223 NA
12: NA 0.1359223 0.0000000
13: NA 0.1359223 0.0000000
14: NA NA 0.0000000
15: 0.0000000 0.0000000 0.0000000
16: 0.0000000 0.0000000 0.0000000
17: 0.0000000 0.0000000 0.0000000
18: 0.0000000 0.0000000 0.0000000
19: 0.0000000 0.0000000 0.0000000
20: NA 0.0000000 NA
使用以下代码可以很好地进行正向替换:
The forward replacement works fine with the following code:
dt$forward <- NA
r <- rle(is.na(dt$Value))
dt$forward <- na.locf(dt$Value, fromLast = F, na.rm = F)
is.na(dt$forward) <- sequence(r$lengths) > 3 & rep(r$values, r$lengths)
但是我不知道如何修改该代码以进行向后替换.我该如何解决?谢谢！
But I don´t know how to modify that code to do the backward replacement. How can I get around this? Thank you!
推荐答案
哈克，但为什么不翻一下专栏呢?
Hacky, but why not just flip your column?
# Using your result as basis
dt$Value <- rev(dt$Value)
dt$backward <- NA
r <- rle(is.na(dt$Value))
dt$backward <- na.locf(dt$Value, fromLast = F, na.rm = F)
is.na(dt$backward) <- sequence(r$lengths) > 3 & rep(r$values, r$lengths)
dt$Value <- rev(dt$Value)
dt$backward <- rev(dt$backward)
结果
> dt
Value forward backward
1: NA NA NA
2: NA NA NA
3: NA NA NA
4: NA NA NA
5: NA NA NA
6: NA NA NA
7: NA NA 0.1359223
8: NA NA 0.1359223
9: NA NA 0.1359223
10: 0.1359223 0.1359223 0.1359223
11: NA 0.1359223 NA
12: NA 0.1359223 0.0000000
13: NA 0.1359223 0.0000000
14: NA NA 0.0000000
15: 0.0000000 0.0000000 0.0000000
16: 0.0000000 0.0000000 0.0000000
17: 0.0000000 0.0000000 0.0000000
18: 0.0000000 0.0000000 0.0000000
19: 0.0000000 0.0000000 0.0000000
20: NA 0.0000000 NA
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