问题
I am trying to extract substrings from a unstructured text. For example, assume a vector of country names:
countries <- c("United States", "Israel", "Canada")
How do I go about passing this vector of character values to extract exact matches from unstructured text.
text.df <- data.frame(ID = c(1:5),
text = c("United States is a match", "Not a match", "Not a match",
"Israel is a match", "Canada is a match"))
In this example, the desired output would be:
ID text
1 United States
4 Israel
5 Canada
So far I have been working with gsub
by where I remove all non-matches and then eliminate then remove rows with empty values. I have also been working with str_extract
from the stringr package, but haven't had success getting the arugments for the regular expression correct. Any assistance would be greatly appreciated!
回答1:
1. stringr
We could first subset the 'text.df' using the 'indx' (formed from collapsing the 'countries' vector) as pattern in 'grep' and then use 'str_extract' the get the pattern elements from the 'text' column, assign that to 'text' column of the subset dataset ('text.df1')
library(stringr)
indx <- paste(countries, collapse="|")
text.df1 <- text.df[grep(indx, text.df$text),]
text.df1$text <- str_extract(text.df1$text, indx)
text.df1
# ID text
#1 1 United States
#4 4 Israel
#5 5 Canada
2. base R
Without using any external packages, we can remove the characters other than those found in 'ind'
text.df1$text <- unlist(regmatches(text.df1$text,
gregexpr(indx, text.df1$text)))
3. stringi
We could also use the faster stri_extract
from stringi
library(stringi)
na.omit(within(text.df, text1<- stri_extract(text, regex=indx)))[-2]
# ID text1
#1 1 United States
#4 4 Israel
#5 5 Canada
回答2:
Here's an approach with data.table
:
library(data.table)
##
R> data.table(text.df)[
sapply(countries, function(x) grep(x,text),USE.NAMES=F),
list(ID, text = countries)]
ID text
1: 1 United States
2: 4 Israel
3: 5 Canada
回答3:
Create the pattern, p
, and use strapply
to extract the match to each component of text
returning NA
for each unmatched component. Finally remove the NA values using na.omit
. This is non-destructive (i.e. text.df
is not modified):
library(gsubfn)
p <- paste(countries, collapse = "|")
na.omit(transform(text.df, text = strapply(paste(text), p, empty = NA, simplify = TRUE)))
giving:
ID text
1 1 United States
4 4 Israel
5 5 Canada
Using dplyr it could also be written as follows (using p
from above):
library(dplyr)
library(gsubfn)
text.df %>%
mutate(text = strapply(paste(text), p, empty = NA, simplify = TRUE)) %>%
na.omit
来源:https://stackoverflow.com/questions/29196831/substring-extraction-from-vector-in-r