我有一个带分类学分配的数据集,我想在新专栏中提取该属。
ActiveWorkbook.SaveAs Filename:=strName & ".csv", FileFormat:=xlUnicodeText
所以这是我的功能(它有效)
library(tidyverse)
library(magrittr)
library(stringr)
df <- structure(list(C043 = c(18361L, 59646L, 27575L, 163L, 863L, 3319L,
0L, 6L), C057 = c(20020L, 97610L, 13427L, 1L, 161L, 237L, 2L,
105L), taxonomy = structure(c(3L, 2L, 1L, 6L, 4L, 4L, 5L, 2L), .Label = c("k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Enterobacter;NA",
"k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Enterobacter;s__cloacae",
"k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Escherichia;s__coli",
"k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Klebsiella;s__",
"k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Pseudomonadales;f__Pseudomonadaceae;g__Pseudomonas;s__",
"k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Pseudomonadales;f__Pseudomonadaceae;g__Pseudomonas;s__stutzeri"
), class = "factor")), .Names = c("C043", "C057", "taxonomy"), row.names = c(1L,
2L, 3L, 4L, 5L, 6L, 8L, 10L), class = "data.frame")
但是当我在extract_genus <- function(str){
genus <- str_split(str, pattern = ";")[[1]][6]
genus %<>% str_sub(start = 4) #%>% as.character
return(genus)
}
(有或没有mutate
)中应用它时,它会在新列中重复第一行值。
as.character
当我使用df %>% mutate(genus = extract_genus(taxonomy))
C043 C057 taxonomy genus
1 18361 20020 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Escherichia;s__coli Escherichia
2 59646 97610 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Enterobacter;s__cloacae Escherichia
3 27575 13427 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Enterobacter;NA Escherichia
4 163 1 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Pseudomonadales;f__Pseudomonadaceae;g__Pseudomonas;s__stutzeri Escherichia
5 863 161 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Klebsiella;s__ Escherichia
(但我不想,我想要一个带有sapply
管道的解决方案)时,它可以正常工作。
dplyr
为什么df_group_gen$genus <- sapply(df_group_gen$taxonomy, extract_genus)
C043 C057 taxonomy genus
1 18361 20020 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Escherichia;s__coli Escherichia
2 59646 97610 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Enterobacter;s__cloacae Enterobacter
3 27575 13427 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Enterobacter;NA Enterobacter
4 163 1 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Pseudomonadales;f__Pseudomonadaceae;g__Pseudomonas;s__stutzeri Pseudomonas
5 863 161 k__Bacteria;p__Proteobacteria;c__Gammaproteobacteria;o__Enterobacteriales;f__Enterobacteriaceae;g__Klebsiella;s__ Klebsiella
无法按照我们的预期进行计算?我发现这个question但没有提供答案,只有有特定的代码。
谢谢:)
答案 0 :(得分:2)
你可以Vectorize
你的函数允许mutate在每一行上发生:
ex_gen <- Vectorize(extract_genus, vectorize.args='str')
df %>% mutate(genus=ex_gen(taxonomy))
或者,您可以使用rowwise
到每行mutate
:
df %>%
rowwise() %>%
mutate(genus = extract_genus(taxonomy))