根据列表中的公共值从data.frame中提取行
我正在寻找一种简单的方法来根据数字序列列表从data.frame中过滤行。
这是一个例子：
我的初始数据框：
data <- data.frame(x=c(0,1,2,0,1,2,3,4,5,12,2,0,10,11,12,13),y="other_data")
我的列表：
list1 <- list(1:5,10:13)
我的目标是只保留来自“数据”的行，其中包含与“数据”的“x”列完全相同的“list1”数字序列。 所以输出data.frame应该是：
finaldata <- data.frame(x=c(1:5,10:13),y="other_data")
任何想法做到这一点？
我开始使用自定义函数来获取一个序列的子集，然后用lapply进行扩展很容易。
#function that takes sequence and a vector
#and returns indices of vector that have complete sequence
get_row_indices<- function(sequence,v){
#get run lengths of whether vector is in sequence
rle_d <- rle(v %in% sequence)
#test if it's complete, so both v in sequence and length of
#matches is length of sequence
select <- rep(length(sequence)==rle_d$lengths &rle_d$values,rle_d$lengths)
return(select)
}
#add row ID to data to show selection
data$row_id <- 1:nrow(data)
res <- do.call(rbind,lapply(list1,function(x){
return(data[get_row_indices(sequence=x,v=data$x),])
}))
res
> res
x y row_id
5 1 other_data 5
6 2 other_data 6
7 3 other_data 7
8 4 other_data 8
9 5 other_data 9
13 10 other_data 13
14 11 other_data 14
15 12 other_data 15
16 13 other_data 16
为什么不使用zoo rollapply ：
library(zoo)
ind = lapply(list1, function(x) {
n = length(x)
which(rollapply(data$x, n, function(y) all(y==x))) + 0:(n-1)
})
data[unlist(ind),]
#x y
#5 1 other_data
#6 2 other_data
#7 3 other_data
#8 4 other_data
#9 5 other_data
#13 10 other_data
#14 11 other_data
#15 12 other_data
#16 13 other_data
extract_fun <- function(x, dat){
# Index where the sequences start
ind <- which(dat == x[1])
# Indexes (within dat) where the sequence should be
ind_seq <- lapply(ind, seq, length.out = length(x))
# Extract the values from dat at the position
dat_val <- mapply(`[`, list(dat), ind_seq)
# Check if values within dat == those in list1
i <- which(as.logical(apply(dat_val, 2, all.equal, x))) # which one is equal?
# Return the correct indices
ind_seq[[i]]
}
获取list1每个项目的索引，并将它们组合到所需的索引中
all_ind <- do.call(c, lapply(list1, extract_fun, data$x))
data[all_ind,]
结果：
x y
5 1 other_data
6 2 other_data
7 3 other_data
8 4 other_data
9 5 other_data
13 10 other_data
14 11 other_data
15 12 other_data
16 13 other_data
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