R-如何在数据框中的两个对应ID之间填充NA

Question

我正在尝试将以下数据集转换为第二个数据集。基本上，我试图在每个ID与该ID之间填写NA。

每个ID对应两个时间戳，我将它们加入了较大的date_time列。出于可复制性的目的，在连接之间执行sql（date_time列非常大），甚至获取原始数据集并在每个id之间创建时间戳，然后将其加入（我有太多的时间），在计算上过于昂贵ID即可）。我已经成功完成了这两种方法，而我拥有的数据量却花费了太多时间。我希望使用此数据集来处理数据。看起来很简单，但这确实让我感到困惑。任何帮助，将不胜感激。

当前数据集：

             date_time     id
                <dttm>  <dbl>
 1 2017-01-30 08:00:00     NA
 2 2017-01-30 08:00:01     NA
 3 2017-01-30 08:00:02     1
 4 2017-01-30 08:00:03     NA
 5 2017-01-30 08:00:04     NA
 6 2017-01-30 08:00:05     NA
 7 2017-01-30 08:00:06     NA
 8 2017-01-30 08:00:07     1
 9 2017-01-30 08:00:08     NA
10 2017-01-30 08:00:09     NA
11 2017-01-30 08:00:10     2
12 2017-01-30 08:00:11     NA
13 2017-01-30 08:00:12     NA
14 2017-01-30 08:00:13     NA
15 2017-01-30 08:00:14     2
16 2017-01-30 08:00:15     NA
17 2017-01-30 08:00:16     3
18 2017-01-30 08:00:17     NA
19 2017-01-30 08:00:18     3
20 2017-01-30 08:00:19     NA

所需数据集：

            date_time     id
                <dttm>  <dbl>
 1 2017-01-30 08:00:00     NA
 2 2017-01-30 08:00:01     NA
 3 2017-01-30 08:00:02     1
 4 2017-01-30 08:00:03     1
 5 2017-01-30 08:00:04     1
 6 2017-01-30 08:00:05     1
 7 2017-01-30 08:00:06     1
 8 2017-01-30 08:00:07     1
 9 2017-01-30 08:00:08     NA
10 2017-01-30 08:00:09     NA
11 2017-01-30 08:00:10     2
12 2017-01-30 08:00:11     2
13 2017-01-30 08:00:12     2
14 2017-01-30 08:00:13     2
15 2017-01-30 08:00:14     2
16 2017-01-30 08:00:15     NA
17 2017-01-30 08:00:16     3
18 2017-01-30 08:00:17     3
19 2017-01-30 08:00:18     3
20 2017-01-30 08:00:19     NA

dput（）日期：

structure(list(date_time = structure(c(1485781200, 1485781201, 
1485781202, 1485781203, 1485781204, 1485781205, 1485781206, 1485781207, 
1485781208, 1485781209, 1485781210, 1485781211, 1485781212, 1485781213, 
1485781214, 1485781215, 1485781216, 1485781217, 1485781218, 1485781219
), class = c("POSIXct", "POSIXt"), tzone = ""), trx_id = c(NA_real_, 
NA_real_, 1, NA_real_, NA_real_, NA_real_, NA_real_, 1, 
NA_real_, NA_real_, 2, NA_real_, NA_real_, NA_real_, 2, 
NA_real_, 3, NA_real_, 3, NA_real_)), .Names = c("date_time", 
"trx_id"), row.names = c(NA, -20L), class = c("tbl_df", "tbl", 
"data.frame"))

Answer 1

一种解决方案可能是使用中的fill功能tidyr。该方法很简单。首先创建2列，每列分别为prev和next值。用于fill在两列中填充缺失值。

现在，对于行这两者具有相同的值prev_val和next_val该值应与被更新prev_val（即装置的那些缺失值是相同数量之间）

df <-  read.table(text = "sl date_time, value
1 '2017-01-30 08:00:00'     NA
2 '2017-01-30 08:00:01'     NA
3 '2017-01-30 08:00:02'     1
4 '2017-01-30 08:00:03'     NA
5 '2017-01-30 08:00:04'     NA
6 '2017-01-30 08:00:05'     NA
7 '2017-01-30 08:00:06'     NA
8 '2017-01-30 08:00:07'     1
9 '2017-01-30 08:00:08'     NA
10 '2017-01-30 08:00:09'     NA
11 '2017-01-30 08:00:10'     2
12 '2017-01-30 08:00:11'     NA
13 '2017-01-30 08:00:12'     NA
14 '2017-01-30 08:00:13'     NA
15 '2017-01-30 08:00:14'     2
16 '2017-01-30 08:00:15'     NA
17 '2017-01-30 08:00:16'     3
18 '2017-01-30 08:00:17'     NA
19 '2017-01-30 08:00:18'     3
20 '2017-01-30 08:00:19'     NA", header = T, stringsAsFactor = F)

#use fill to find missing values
df %>%
  mutate(prev_val = (value), next_val = (value)) %>%
  fill(prev_val, .direction = "down") %>%
  fill(next_val, .direction = "up") %>%
  mutate(value = ifelse(prev_val == next_val, prev_val, value )) %>%
  select(-prev_val, -next_val)

Result:
   sl          date_time. value
1   1 2017-01-30 08:00:00    NA
2   2 2017-01-30 08:00:01    NA
3   3 2017-01-30 08:00:02     1
4   4 2017-01-30 08:00:03     1
5   5 2017-01-30 08:00:04     1
6   6 2017-01-30 08:00:05     1
7   7 2017-01-30 08:00:06     1
8   8 2017-01-30 08:00:07     1
9   9 2017-01-30 08:00:08    NA
10 10 2017-01-30 08:00:09    NA
11 11 2017-01-30 08:00:10     2
12 12 2017-01-30 08:00:11     2
13 13 2017-01-30 08:00:12     2
14 14 2017-01-30 08:00:13     2
15 15 2017-01-30 08:00:14     2
16 16 2017-01-30 08:00:15    NA
17 17 2017-01-30 08:00:16     3
18 18 2017-01-30 08:00:17     3
19 19 2017-01-30 08:00:18     3
20 20 2017-01-30 08:00:19    NA