使用同一数据框中的数据填充data.frame中的缺失值 [英] Fill missing values in the data.frame with the data from the same data frame
本文介绍了使用同一数据框中的数据填充data.frame中的缺失值的处理方法，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
我看起来像...
（没有行）的数据框双方为NA，表按日期排序）。
日期XY
2012-07-05 00 ：01：19 0.0122 NA
2012-07-05 03:19:34 0.0121 NA
2012-07-05 03:19:56 0.0121 0.027
2012-07-05 03:20 ：31 0.0121 NA
2012-07-05 04:19:56 0.0121 0.028
2012-07-05 04:20:31 0.0121 NA
2012-07-05 04:20:50 0.0121 NA
2012-07-05 04:22:29 0.0121 0.027
2012-07-05 04:24:37 0.0121 NA
2012-07-05 20:48:45 0.0121 NA
2012-07-05 23:02:34 NA 0.029
2012-07-05 23:30:45 NA 0.029
与此，我正在寻找..
- 保留非数据丢失行因为它是。
- 如果任一方都缺少（NA），则填写最近的前一个具有有效对端值的行。
所以结果，我想让表看起来像...
日期XY
2012-07-05 00:01:19 0.0122 NA
2012-07-05 03:19:34 0.0121 NA
2012-07-05 03:19:56 0.0121 0.027
2012-07-05 03:20:31 0.0121 0.027
2012-07-05 04： 19:56 0.0121 0.028
2012-07-05 04:20:31 0.0121 0.028
2012-07-05 04:20:50 0.0121 0.028
2012-07-05 04:22： 29 0.0121 0.027
2012-07-05 04:24:37 0.0121 0.027
2012-07-05 20:48:45 0.0121 0.027
2012-07-05 23:02:34 0.0121 0.029
2012-07-05 23:30:45 0.0121 0.029
什么样的R命令可以用来实现吗？
解决方案
使用 na.locf 从动物园包
dat < - read.table =2012-07-05 00:01:19 0.0122 NA
2 012-07-05 03:19:34 0.0121 NA
2012-07-05 03:19:56 0.0121 0.027
2012-07-05 03:20:31 0.0121 NA
2012- 07-05 04:19:56 0.0121 0.028
2012-07-05 04:20:31 0.0121 NA
2012-07-05 04:20:50 0.0121 NA
2012-07- 05 04:22:29 0.0121 0.027
2012-07-05 04:24:37 0.0121 NA
2012-07-05 20:48:45 0.0121 NA
2012-07-05 23 ：02：34 NA 0.029
2012-07-05 23:30:45 NA 0.029）
require（zoo）
na.locf（dat）
＃V1 V2 V3 V4
＃1 2012-07-05 00:01:19 0.0122< NA>
＃2 2012-07-05 03:19:34 0.0121< NA>
＃3 2012-07-05 03:19:56 0.0121 0.027
＃4 2012-07-05 03:20:31 0.0121 0.027
＃5 2012-07-05 04:19 ：56 0.0121 0.028
＃6 2012-07-05 04:20:31 0.0121 0.028
＃7 2012-07-05 04:20:50 0.0121 0.028
＃8 2012-07- 05 04:22:29 0.0121 0.027
＃9 2012-07-05 04:24:37 0.0121 0.027
＃10 2012-07-05 20:48:45 0.0121 0.027
＃11 2012-07-05 23:02:34 0.0121 0.029
＃12 2012-07-05 23:30:45 0.0121 0.029
I'm trying to backfill a fully outerjoined table with nearest preceding column data.
The data frame I have looks like.. (No rows have both sides as NA and the table is sorted by date).
date X Y
2012-07-05 00:01:19 0.0122 NA
2012-07-05 03:19:34 0.0121 NA
2012-07-05 03:19:56 0.0121 0.027
2012-07-05 03:20:31 0.0121 NA
2012-07-05 04:19:56 0.0121 0.028
2012-07-05 04:20:31 0.0121 NA
2012-07-05 04:20:50 0.0121 NA
2012-07-05 04:22:29 0.0121 0.027
2012-07-05 04:24:37 0.0121 NA
2012-07-05 20:48:45 0.0121 NA
2012-07-05 23:02:34 NA 0.029
2012-07-05 23:30:45 NA 0.029
with this, I'm looking to..
- leave the non-data missing rows as it is.
- If either one side is missing (NA), then fill it with the "nearest preceding" row which has valid opposite side's value.
And so as the result, I would like to have the table looking like...
date X Y
2012-07-05 00:01:19 0.0122 NA
2012-07-05 03:19:34 0.0121 NA
2012-07-05 03:19:56 0.0121 0.027
2012-07-05 03:20:31 0.0121 0.027
2012-07-05 04:19:56 0.0121 0.028
2012-07-05 04:20:31 0.0121 0.028
2012-07-05 04:20:50 0.0121 0.028
2012-07-05 04:22:29 0.0121 0.027
2012-07-05 04:24:37 0.0121 0.027
2012-07-05 20:48:45 0.0121 0.027
2012-07-05 23:02:34 0.0121 0.029
2012-07-05 23:30:45 0.0121 0.029
What kind of R commands can I use to achieve this?
解决方案
Use na.locf from the zoo package
dat <- read.table(text="2012-07-05 00:01:19 0.0122 NA
2012-07-05 03:19:34 0.0121 NA
2012-07-05 03:19:56 0.0121 0.027
2012-07-05 03:20:31 0.0121 NA
2012-07-05 04:19:56 0.0121 0.028
2012-07-05 04:20:31 0.0121 NA
2012-07-05 04:20:50 0.0121 NA
2012-07-05 04:22:29 0.0121 0.027
2012-07-05 04:24:37 0.0121 NA
2012-07-05 20:48:45 0.0121 NA
2012-07-05 23:02:34 NA 0.029
2012-07-05 23:30:45 NA 0.029")
require("zoo")
na.locf(dat)
# V1 V2 V3 V4
#1 2012-07-05 00:01:19 0.0122 <NA>
#2 2012-07-05 03:19:34 0.0121 <NA>
#3 2012-07-05 03:19:56 0.0121 0.027
#4 2012-07-05 03:20:31 0.0121 0.027
#5 2012-07-05 04:19:56 0.0121 0.028
#6 2012-07-05 04:20:31 0.0121 0.028
#7 2012-07-05 04:20:50 0.0121 0.028
#8 2012-07-05 04:22:29 0.0121 0.027
#9 2012-07-05 04:24:37 0.0121 0.027
#10 2012-07-05 20:48:45 0.0121 0.027
#11 2012-07-05 23:02:34 0.0121 0.029
#12 2012-07-05 23:30:45 0.0121 0.029
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