Detecting multiple strings with dplyr and stringr
I am trying to combine dplyr and stringr to discover multiple patterns in a dataframe. I want to use dplyr as I want to test several different columns.
Here are some sample data:
test.data <- data.frame(item = c("Apple", "Bear", "Orange", "Pear", "Two Apples"))
fruit <- c("Apple", "Orange", "Pear")
test.data
item
1 Apple
2 Bear
3 Orange
4 Pear
5 Two Apples
What I would like to use is something like:
test.data <- test.data %>% mutate(is.fruit = str_detect(item, fruit))
and get
item is.fruit
1 Apple 1
2 Bear 0
3 Orange 1
4 Pear 1
5 Two Apples 1
Very simple test work
> str_detect("Apple", fruit)
[1] TRUE FALSE FALSE
> str_detect("Bear", fruit)
[1] FALSE FALSE FALSE
But I can't seem to get this to work on a dataframe column, even without dplyr:
> test.data$is.fruit <- str_detect(test.data$item, fruit)
Error in check_pattern(pattern, string) :
Lengths of string and pattern not compatible
Does anyone know how to do this?
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2 answers
str_detect
only accepts a pattern of length-1. Either translate it into a single regex with paste(..., collapse = '|')
, or use any
:
sapply(test.data$item, function(x) any(sapply(fruit, str_detect, string = x)))
# Apple Bear Orange Pear Two Apples
# TRUE FALSE TRUE TRUE TRUE
str_detect(test.data$item, paste(fruit, collapse = '|'))
# [1] TRUE FALSE TRUE TRUE TRUE
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This simple approach works great for EXACT compliance:
test.data %>% mutate(is.fruit = item %in% fruit)
# A tibble: 5 x 2
item is.fruit
<chr> <lgl>
1 Apple TRUE
2 Bear FALSE
3 Orange TRUE
4 Pear TRUE
5 Two Apples FALSE
This approach works for partial match (as the question is asking):
test.data %>%
rowwise() %>%
mutate(is.fruit = sum(str_detect(item, fruit)))
Source: local data frame [5 x 2]
Groups: <by row>
# A tibble: 5 x 2
item is.fruit
<chr> <int>
1 Apple 1
2 Bear 0
3 Orange 1
4 Pear 1
5 Two Apples 1
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