R：如何提高 grepl 在 dataframe 中应用函数的性能

Question

我有以下列的数据框：

country<- c("CA","IN","US")
text   <- c("paint red green", "painting red", "painting blue")
word   <- c("green, red, blue", "red", "red, blue")
df     <- data.frame(country, text, word)

对于每一行，我想在文本列的文本中找到单词列中的单词，并将它们呈现在一个新的列中，这样就会显示文本中创建的单词，以逗号分隔。所以新列应该是：

df$new_col   <- c("green,red","red","blue")

我正在使用这几行代码，但是它需要很长时间才能运行甚至崩溃。

setDT(df)[, new_col:= paste(df$word[unlist(lapply(df$word,function(x) grepl(x, df$text,
     ignore.case = T)))], collapse = ","), by = 1:nrow(df)]

有没有办法更改代码以提高效率？

非常感谢！

Answer 1

试试这个

mapply(function(x,y){paste(intersect(x,y),collapse=", ")},
       strsplit(as.character(df$text),"\, | "),
       strsplit(as.character(df$word),"\, | "))

[1] "red, green" "red"        "blue"

Answer 2

library(tidyverse)    
df %>% 
   mutate(newcol = stringr::str_extract_all(text,gsub(", +","|",word)))
      country            text             word     newcol
    1      CA paint red green green, red, blue red, green
    2      IN    painting red              red        red
    3      US   painting blue        red, blue       blue

在这种情况下，newcol 是一个列表。要使它成为一个字符串，我们可以这样做：

df%>%
  mutate(newcol = text %>%
           str_extract_all(gsub(", +", "|", word)) %>%
           invoke(toString, .))

使用 data.table，您可以：

 df[,id := .I][,newcol := do.call(toString,str_extract_all(text,gsub(', +',"|",word))),
      by = id][, id := NULL][]
   country            text             word     newcol
1:      CA paint red green green, red, blue red, green
2:      IN    painting red              red        red
3:      US   painting blue        red, blue       blue

Answer 3

另一个使用 mapply + grep + regmatches 的基础 R 解决方案，即

df <- within(df, newcol <- mapply(function(x,y) toString(grep(x,y,value = TRUE)), 
                                  gsub("\W+","|",word), 
                                  regmatches(text,gregexpr("\w+",text))))

这样

> df
  country            text             word     newcol
1      CA paint red green green, red, blue red, green
2      IN    painting red              red        red
3      US   painting blue        red, blue       blue

R：如何提高 grepl 在 dataframe 中应用函数的性能

R: How to improve performance of grepl in apply function within dataframe

performance

r

lapply

dataframe

grepl