R Column Check If Contains Value from Another Column

R - If column contains a string from vector, append flag into another column

Update:
If a list is preferred: Using str_extract_all:

df %>%  
  transmute(across(-id, ~case_when(str_detect(., pattern) ~ str_extract_all(., pattern)), .names = "new_col{col}")) 

gives:

  new_colonetext new_colcop new_coltext3
  <list>         <list>     <list>      
1 <chr [1]>      <NULL>     <chr [2]>   
2 <chr [2]>      <chr [2]>  <NULL>      
3 <chr [2]>      <chr [4]>  <chr [5]>  

Here is how you could achieve the result:

1. create a pattern of the vector
2. use mutate across to check the needed columns
3. if the desired string is detected then extract to a new column !

myvec <- c("cat", "dog", "bird")

pattern <- paste(myvec, collapse="|")

library(dplyr)
library(tidyr)
df %>% 
  mutate(across(-id, ~case_when(str_detect(., pattern) ~ str_extract_all(., pattern)), .names = "new_col{col}")) %>% 
  unite(topic, starts_with('new'), na.rm = TRUE, sep = ',')

    id onetext                cop                                                                        text3                                                                              topic                                     
  <dbl> <chr>                  <chr>                                                                      <chr>                                                                              <chr>                                     
1     1 cat furry pink british Little Grey Cat is the nickname given to a kitten of the British Shorthai~ On October 4th the first single topic blog devoted to the little grey cat was lau~ "cat,NULL,c(\"cat\", \"cat\")"            
2     2 dog cat fight          Dogs have soft fur and tails so do cats Do cats like to chase their tails  there are many fights going on and this is just an example text                    "c(\"dog\", \"cat\"),c(\"cat\", \"cat\"),~
3     3 bird cat issues        A cat and bird can coexist in a home but you will have to take certain me~ Some cats will not care about a pet bird at all while others will make it its lif~ "c(\"bird\", \"cat\"),c(\"cat\", \"bird\"~                                                                                    

check if column contains part of another column in r

You can do this in this way:

df <- data.frame(a,b,stringsAsFactors = F)

for (i in seq(1,nrow(df))){
    if (df$a[i] == '' || length(agrep(df$a[i],df$b[i])) > 0)
        df$c[i] <- 'update'
    else
        df$c[i] <- 'insert'
}

df

##       a      b      c
##1 0c1234 Oc1234 update
##2        Oc5678 update
##3  2468O Oc9123 insert

Filter for column value if another column contains a value

We can use a group_by filter here

library(dplyr)
my_df %>%
   group_by(x) %>% 
   filter(if(any(y == 1)) y == 1 else TRUE)
# A tibble: 4 x 2
# Groups:   x [2]
#      x     y
#  <dbl> <dbl>
#1     1     1
#2     2     4
#3     2     5
#4     2     6

Or if it doesn't needs to be group by

my_df %>%
   filter( (x == 1 & y == 1)|(x !=1))

---

Or with subset

subset(my_df,  (x == 1 & y == 1)|(x !=1))
#  x y
#1 1 1
#4 2 4
#5 2 5
#6 2 6

Or

subset(my_df,  (x == 1 & y == 1)|(x !=1 & y != 1))

Check whether values in one data frame column exist in a second data frame

Use %in% as follows

A$C %in% B$C

Which will tell you which values of column C of A are in B.

What is returned is a logical vector. In the specific case of your example, you get:

A$C %in% B$C
# [1]  TRUE FALSE  TRUE  TRUE

Which you can use as an index to the rows of A or as an index to A$C to get the actual values:

# as a row index
A[A$C %in% B$C,  ]  # note the comma to indicate we are indexing rows

# as an index to A$C
A$C[A$C %in% B$C]
[1] 1 3 4  # returns all values of A$C that are in B$C

We can negate it too:

A$C[!A$C %in% B$C]
[1] 2   # returns all values of A$C that are NOT in B$C

---

If you want to know if a specific value is in B$C, use the same function:

  2 %in% B$C   # "is the value 2 in B$C ?"  
  # FALSE

  A$C[2] %in% B$C  # "is the 2nd element of A$C in B$C ?"  
  # FALSE

Find column value contained in another column R

We split the second and third column by one or more space (\\s+), then paste the union of the corresponding rows with mapply to create the 'combined'

lst <- lapply(df[2:3], function(x) strsplit(as.character(x), "\\s+"))
df$combined <- mapply(function(x,y) paste(union(x, y), collapse=" "), lst$add1, lst$add2)
df$combined
#[1] "21ST AVE BLAH ST"      "5TH ST EAST BLAH BLVD"

---

Or another option is gsub

gsub("((\\w+\\s*){2,})\\1", "\\1", do.call(paste, df[2:3]))
#[1] "21ST AVE BLAH ST"      "5TH ST EAST BLAH BLVD"

Check if column contains value from a list and assign that value to new column

Paste the base_patters together and use str_extract to extract any pattern present in mynames.

library(data.table)
library(stringr)

transformations[,pattern := str_extract(mynames,str_c(base_patters,collapse = "|"))]

#         mynames pattern
#1:    HI_pat1_jo    pat1
#2: A2_a4_pat1_LN    pat1
#3:       pat3_LN    pat3

R function that detects if a dataframe column contains string values from another dataframe column and adds a column that contains the detected str

First you could a column for each of the possible categories to the dataframe with the names, as placeholders (just filled with NA). Then for each of those columns, check whether the column name (so the category) appears in the name. Turn it into a long dataframe, and then remove the FALSE rows -- those that didn't detect the category in the name.

library(tidyverse)

df1 <- tribble(
  ~name,
  "Apple page",
  "Mango page",
  "Lychee juice",
  "Cranberry club"
)
df2 <- tribble(
  ~fruit,
  "Apple",
  "Grapes",
  "Strawberry",
  "Mango",
  "lychee",
  "cranberry"
)

fruits <- df2$fruit %>%
  str_to_lower() %>% 
  set_names(rep(NA_character_, length(.)), .)

df1 %>% 
  add_column(!!!fruits) %>% 
  mutate(across(-name, ~str_detect(str_to_lower(name), cur_column()))) %>% 
  pivot_longer(-name, names_to = "category") %>% 
  filter(value) %>% 
  select(-value)

#> # A tibble: 4 × 2
#>   name           category 
#>   <chr>          <chr>    
#> 1 Apple page     apple    
#> 2 Mango page     mango    
#> 3 Lychee juice   lychee   
#> 4 Cranberry club cranberry

R modify value in one column if content in another column contains string

Try this function:

subtract_match <- function(column1, column2, text, df) {
  df2 <- df
  df2[, column2] <- ifelse(grepl(text, df[, column1]), 
                           df[, column2] - nchar(text), 
                           df[, column2])
  df2
}

subtract_match("test", "testcount", "two", df1)

    test    hyp testcount hypcount
1    one    two         3        3
2    two    one         0        3
3  three onetwo         5        6
4    one    one         3        3
5 onetwo    two         3        3

subtract_match("hyp", "hypcount", "two", df1)

    test    hyp testcount hypcount
1    one    two         3        0
2    two    one         3        3
3  three onetwo         5        3
4    one    one         3        3
5 onetwo    two         6        0

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