Question

我有以下列名称向量：

plot_variables <- c("Ser predicted (g/L)", "Ser initial (g/L)", "Ser experimental (g/L)", "Glu predicted (g/L)", "Glu initial (g/L)", "Glu experimental (g/L)", Pro predicted (g/L), ...)

我有一个短名称的词汇表：

df_glossary <- data.frame(
  short = c("Cys", "Pro", "Phe", "Ser", "Glu", "Glc", ...),
  full = c("Cysteine", "Proline", "Phenylalanine", "Serine", "Glutamate", "Glucose", ...),
  stringsAsFactors = FALSE
)

我想匹配这两个，并有类似的东西：

names_matching <- data.frame(
variable = c("Ser predicted (g/L)", "Ser initial (g/L)", "Ser experimental (g/L)", ...),
label = c("Serine predicted (g/L)", "Serine initial (g/L)", "Serine experimental (g/L)", ...)
)

有没有比这更优雅的方式：

pl<-unlist(plot_variables)

pl<-sapply(1:nrow(df_glossary) , function(x){
    pl<<- gsub(df_glossary$short[x], df_glossary$full[x],  pl, fixed = TRUE)
    })

pl <- pl[,nrow(df_glossary)] %>% data.frame()

names_matching <- cbind(plot_variables %>% data.frame, pl)

Answer 1

我认为您在gsubfn包裹中寻找的是gsubfn。如果你想从另一个数据框中读取键和值，你可以做一些争论，但一般来说这里是如何工作的：

> library(gsubfn)
> gsubfn('[Ser|Glu|Pro]*', 
     list('Ser'='Serine','Glu'='Glutamate','Pro'='Proline'), plot_variables)
[1] "Serine predicted (g/L)"       "Serine initial (g/L)"        
[3] "Serine experimental (g/L)"    "Glutamate predicted (g/L)"   
[5] "Glutamate initial (g/L)"      "Glutamate experimental (g/L)"
[7] "Proline predicted (g/L)"

Answer 2

我不确定我理解这个问题，这会有用吗？

df_glossary <- data.frame(
  shortnames = c("Cys", "Pro", "Phe", "Ser", "Glu", "Glc"),
  full = c("Cysteine", "Proline", "Phenylalanine", "Serine", "Glutamate", "Glucose"),
  stringsAsFactors = FALSE
)
plot_variables <- c("Ser predicted (g/L)", "Ser initial (g/L)", "Ser experimental (g/L)", "Glu predicted (g/L)", "Glu initial (g/L)", "Glu experimental (g/L)", "Pro predicted (g/L)")
suffixes = c("predicted (g/L)", "initial (g/L)", "experimental (g/L)")

df_glossary %>% rowwise %>% 
    do(data.frame(short=.$short, full=.$full, suffix=suffixes )) %>%
    mutate(label=paste(full, suffix))

short   full    suffix  label
Cys Cysteine    predicted (g/L) Cysteine predicted (g/L)
Cys Cysteine    initial (g/L)   Cysteine initial (g/L)
Cys Cysteine    experimental (g/L)  Cysteine experimental (g/L)
Pro Proline predicted (g/L) Proline predicted (g/L)
Pro Proline initial (g/L)   Proline initial (g/L)
Pro Proline experimental (g/L)  Proline experimental (g/L)
Phe Phenylalanine   predicted (g/L) Phenylalanine predicted (g/L)
Phe Phenylalanine   initial (g/L)   Phenylalanine initial (g/L)
Phe Phenylalanine   experimental (g/L)  Phenylalanine experimental (g/L)
Ser Serine  predicted (g/L) Serine predicted (g/L)
Ser Serine  initial (g/L)   Serine initial (g/L)
Ser Serine  experimental (g/L)  Serine experimental (g/L)
Glu Glutamate   predicted (g/L) Glutamate predicted (g/L)
Glu Glutamate   initial (g/L)   Glutamate initial (g/L)
Glu Glutamate   experimental (g/L)  Glutamate experimental (g/L)
Glc Glucose predicted (g/L) Glucose predicted (g/L)
Glc Glucose initial (g/L)   Glucose initial (g/L)
Glc Glucose experimental (g/L)  Glucose experimental (g/L)

R在循环中使用gsub

2 个答案: