我有一个data.frame
我想(按行)将子集划分为(重叠)“批次”,然后将purrr:::map
这些批次划分为一个函数。在下面的示例中,d
是data.frame
我想要子集和批处理:
set.seed(19)
n1 <- data.frame(c0= "N",c1 = rep("A",4),c2 = rep(c("i","j"),2), num = rnorm(4))
n2 <- data.frame(c0= "N", c1 = rep("B",6),c2 = rep(c("i","j"),3), num = rnorm(3))
y1 <- data.frame(c0 = "Y", c1 = rep("A",2),c2 = c("i","j"), num = rnorm(2))
y2 <- data.frame(c0 = "Y", c1 = rep("B",4),c2 = rep(c("i","j"),each = 2), num = rnorm(2))
d <- rbind(y1,y2,n1,n2)
这是d
# c0 c1 c2 num
# 1 Y A i -0.7447795
# 2 Y A j -0.2597870
# 3 Y B i -0.1830838
# 4 Y B i 0.5186300
# 5 Y B j -0.1830838
# 6 Y B j 0.5186300
# 7 N A i -1.1894537
# 8 N A j 0.3885812
# 9 N A i -0.3443333
# 10 N A j -0.5478961
# 11 N B i 0.9806622
# 12 N B j -0.2366460
# 13 N B i 0.8097397
# 14 N B j 0.9806622
# 15 N B i -0.2366460
# 16 N B j 0.8097397
子集化配方是
- 子集
c0
-> 给组Y
和N
- 在
c0=="N"
子集中通过c1
--> 给组NA
,NB
- 子集
NA
和NB
通过c2
--> 给组NAi
,NAj
,NBi
,NBj
- row_bind
N?i
toY?i
andN?j
toY?j
(where?
isA
orB
) --> 给出最后的 4 个数据子集
在 R 中:
subset.Yi <- d %>% filter(c0=="Y"& c2=="i")
subset.Yj <- d %>% filter(c0=="Y"& c2=="j")
list(
d1 = d %>% filter(c0=="N" & c1 == "A", c2 == "i") %>% rbind(subset.Yi),
d2 = d %>% filter(c0=="N" & c1 == "B", c2 == "i") %>% rbind(subset.Yi),
d3 = d %>% filter(c0=="N" & c1 == "A", c2 == "j") %>% rbind(subset.Yj),
d4 = d %>% filter(c0=="N" & c1 == "B", c2 == "j") %>% rbind(subset.Yj)
) %>%
tibble::tibble(batches = paste0("batch",1:length(.)),data = .) ->tmp
如果匹配c2
不重要,我可以执行以下操作:
d %>% filter(.,c0 == "N") %>%
group_by(.,c1) %>%
do(batches = rbind(d[d$c0=="Y"],.)) -> tmp
但这还不是。先感谢您!顺便说一句,我知道tidyverse
这在外面是可行的,但是当我为我tidyverse
的其余代码采用方案时,我希望保持一致。