如何使用 str_split_fixed 拆分具有多个分隔符的数据框?
How to split data frame with multiple delimiter using str_split_fixed?
如何将由多个定界符分隔的列拆分为数据框中的单独列
read.table(text = " Chr Nm1 Nm2 Nm3
chr10_100064111-100064134+Nfif 20 20 20
chr10_100064115-100064138-Kitl 30 19 40
chr10_100076865-100076888+Tert 60 440 18
chr10_100079974-100079997-Itg 50 11 23
chr10_100466221-100466244+Tmtc3 55 24 53", header = TRUE)
Chr gene Nm1 Nm2 Nm3
chr10_100064111-100064134 Nfif 20 20 20
chr10_100064115-100064138 Kitl 30 19 40
chr10_100076865-100076888 Tert 60 440 18
chr10_100079974-100079997 Itg 50 11 23 12
chr10_100466221-100466244 Tmtc3 55 24 53 12
我用过
library(stringr)
df2 <- str_split_fixed(df1$name, "\+", 2)
我想知道如何同时包含 + 和 - 分隔符
这应该有效:
str_split_fixed(a, "[-+]", 2)
这里有一种在 base R 中使用 strsplit
:
执行此操作的方法
# split Chr into a list
tempList <- strsplit(as.character(df$Chr), split="[+-]")
# replace Chr with desired values
df$Chr <- sapply(tempList, function(i) paste(i[[1]], i[[2]], sep="-"))
# get Gene variable
df$gene <- sapply(tempList, "[[", 3)
如果您想将一列拆分为多列,tidyr::separate
很方便:
library(tidyr)
dat %>% separate(Chr, into = paste0('Chr', 1:3), sep = '[+-]')
# Chr1 Chr2 Chr3 Nm1 Nm2 Nm3
# 1 chr10_100064111 100064134 Nfif 20 20 20
# 2 chr10_100064115 100064138 Kitl 30 19 40
# 3 chr10_100076865 100076888 Tert 60 440 18
# 4 chr10_100079974 100079997 Itg 50 11 23
# 5 chr10_100466221 100466244 Tmtc3 55 24 53
如何将由多个定界符分隔的列拆分为数据框中的单独列
read.table(text = " Chr Nm1 Nm2 Nm3
chr10_100064111-100064134+Nfif 20 20 20
chr10_100064115-100064138-Kitl 30 19 40
chr10_100076865-100076888+Tert 60 440 18
chr10_100079974-100079997-Itg 50 11 23
chr10_100466221-100466244+Tmtc3 55 24 53", header = TRUE)
Chr gene Nm1 Nm2 Nm3
chr10_100064111-100064134 Nfif 20 20 20
chr10_100064115-100064138 Kitl 30 19 40
chr10_100076865-100076888 Tert 60 440 18
chr10_100079974-100079997 Itg 50 11 23 12
chr10_100466221-100466244 Tmtc3 55 24 53 12
我用过
library(stringr)
df2 <- str_split_fixed(df1$name, "\+", 2)
我想知道如何同时包含 + 和 - 分隔符
这应该有效:
str_split_fixed(a, "[-+]", 2)
这里有一种在 base R 中使用 strsplit
:
# split Chr into a list
tempList <- strsplit(as.character(df$Chr), split="[+-]")
# replace Chr with desired values
df$Chr <- sapply(tempList, function(i) paste(i[[1]], i[[2]], sep="-"))
# get Gene variable
df$gene <- sapply(tempList, "[[", 3)
如果您想将一列拆分为多列,tidyr::separate
很方便:
library(tidyr)
dat %>% separate(Chr, into = paste0('Chr', 1:3), sep = '[+-]')
# Chr1 Chr2 Chr3 Nm1 Nm2 Nm3
# 1 chr10_100064111 100064134 Nfif 20 20 20
# 2 chr10_100064115 100064138 Kitl 30 19 40
# 3 chr10_100076865 100076888 Tert 60 440 18
# 4 chr10_100079974 100079997 Itg 50 11 23
# 5 chr10_100466221 100466244 Tmtc3 55 24 53