问题描述
假设我有一个数据框:
df <- data.frame(group = c('A','A','A','B','B','B'),
time = c(1,2,4,1,2,3),
data = c(5,6,7,8,9,10))
我想要做的是将数据插入序列中缺少的数据框中.因此，在上面的示例中，我缺少组 A 的 time = 3 和组 B 的 time = 4 的数据.我基本上想在data 列的位置.
What I want to do is insert data into the data frame where it was missing in the sequence. So in the above example, I'm missing data for time = 3 for group A, and time = 4 for Group B. I would essentially want to put 0's in the place of the data column.
我将如何添加这些额外的行?
How would I go about adding these additional rows?
目标是:
df <- data.frame(group = c('A','A','A','A','B','B','B','B'),
time = c(1,2,3,4,1,2,3,4),
data = c(5,6,0,7,8,9,10,0))
我的真实数据是几千个数据点，所以手动这样做是不可能的.
My real data is a couple thousand data points, so manually doing so isn't possible.
推荐答案
你可以试试merge/expand.grid
res <- merge(
expand.grid(group=unique(df$group), time=unique(df$time)),
df, all=TRUE)
res$data[is.na(res$data)] <- 0
res
# group time data
#1 A 1 5
#2 A 2 6
#3 A 3 0
#4 A 4 7
#5 B 1 8
#6 B 2 9
#7 B 3 10
#8 B 4 0
或者使用data.table
library(data.table)
setkey(setDT(df), group, time)[CJ(group=unique(group), time=unique(time))
][is.na(data), data:=0L]
# group time data
#1: A 1 5
#2: A 2 6
#3: A 3 0
#4: A 4 7
#5: B 1 8
#6: B 2 9
#7: B 3 10
#8: B 4 0
更新
正如评论中提到的@thelatemail，如果所有组中都不存在特定的时间"值，上述方法将失败.可能这会更笼统.
Update
As @thelatemail mentioned in the comments, the above method would fail if a particular 'time' value is not present in all the groups. May be this would be more general.
res <- merge(
expand.grid(group=unique(df$group),
time=min(df$time):max(df$time)),
df, all=TRUE)
res$data[is.na(res$data)] <- 0
并在 data.table 解决方案中将 time=unique(time) 替换为 time= min(time):max(time).
and similarly replace time=unique(time) with time= min(time):max(time) in the data.table solution.
这篇关于将缺失的时间行插入数据框中的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！