Multiple Strings with Str_Detect R

str_detect for multiple patterns

You need to use the | separator in your search, all within one set of "".

> words <- c("quantity", "single", "double", "triple", "awful")
> set.seed(1234)
> df = tibble(col = sample(words,10, replace = TRUE))
> df
# A tibble: 10 x 1
   col     
   <chr>   
 1 triple  
 2 single  
 3 awful   
 4 triple  
 5 quantity
 6 awful   
 7 triple  
 8 single  
 9 single  
10 triple 

> df %>% filter(str_detect(col, "quantity|single"))
# A tibble: 4 x 1
  col     
  <chr>   
1 single  
2 quantity
3 single  
4 single  

Ignore case with multiple strings using str_detect in R

A possible solution would be to bring everything to lower case and match that with ag|field.

dat %>%
  mutate(Class_2 = case_when(
    str_detect(string = str_to_lower(Class),
               pattern = "ag|field") ~ "Agricultural",
    TRUE ~ Class
  ))

# A tibble: 3 × 2
  Class              Class_2     
  <chr>              <chr>       
1 ag                 Agricultural
2 Agricultural--misc Agricultural
3 old field          Agricultural

how to use str_detect within across when searching multiple columns for several search strings

Combine across with Reduce to select rows which has any occurrence of the pattern.

library(dplyr)
library(stringr)

pat <- paste(search_string, collapse = "|")

raw_df %>% 
  filter(Reduce(`|`, across(c(cust_name, other_desc), 
        ~str_detect(., regex(pat, ignore_case = TRUE)))))

However, I think using if_any is more suitable here as it was build to handle such cases -

raw_df %>%
  filter(if_any(c(cust_name, other_desc), 
                ~str_detect(., regex(pat, ignore_case = TRUE))))

# cust_name other_desc trans   val
#  <chr>     <chr>      <chr> <int>
#1 Cisco     nothing    a       100
#2 bad_cs    cisCo      s       101
#3 Ibm       nothing    d       102
#4 bad_ib    ibM        f       102

str_detect with multiple strings (and not or) of the same kind using R

You may use -

library(stringr)

str_detect(find.variable, '\\bdetect\\b.*\\bdetect\\b')
#[1]  TRUE FALSE FALSE  TRUE FALSE

If you want to allow consecutive values of 'detect', use

str_detect(find.variable, 'detect.*detect')

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You can also use str_count to count number of detects in a string.

str_count(find.variable, 'detect') == 2
#[1]  TRUE FALSE FALSE  TRUE  TRUE

Note that the last value is TRUE in case of str_count.

Detect multiple strings with dplyr and stringr

str_detect only accepts a length-1 pattern. Either turn it into one regex using 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

Filter by multiple patterns with filter() and str_detect()

The correct syntax to accomplish this with filter() and str_detect() would be

df %>%
  filter(
      str_detect(letters, "a|f|o")
  )
#  numbers letters
#1       1       a
#2       6       f
#3      15       o
#4      27       a
#5      32       f
#6      41       o

R exact match for multiple patterns

We could use the word boundary (\\b) to avoid the unnecessary partial matches

str_detect(myfile,paste0("\\b(", paste(toMatch, collapse="|"), ")\\b"))
 [1]  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE

---

Based on the elements used, it can be done with %in%

myfile %in% toMatch
1]  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE

summarise to sum cells containing multiple strings

Use str_detect separately for & condition.

library(dplyr)
library(stringr)

summarise("Total" = n(),
          "CD8:PD-1" = sum(str_detect(ordered, "PD-1") & 
                           str_detect(ordered, "CD8"),na.rm = TRUE),
          "CD8:PD:1:FoxP3" = sum(str_detect(ordered, "PD-1") & 
                                 str_detect(ordered, "CD8") &
                                 str_detect(ordered, "FoxP3"), na.rm = TRUE))

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