Creating a column based off of multiple columns

Question

I have a data set with multiple columns. A sample of the first three columns are as follows:

df$a1 <- c("00845", "486", "49392", "04186", "5990")

df$a2 <- c("34580", "**2761**", "27800", "4439", "5849")

df$a3 <- c("0340", "49392", "78831", "70714", "486")

I want to create a column df$b which gives me a "1" if any of the columns a1-a15 contain the string "2761".

a1	a2	a3	...	a15	b
00845	34580	0340	...	4280	0
486	2761	49392	...	25000	1
49392	27800	78831	...	7955	0
04186	4439	70714	...	27800	0
5990	5849	486	...	4400	0

So far, I've developed the following code:

df %>%

  mutate(d = c(0, 1)[(a1:a15 %in% c("2761")) + 1])

but it doesn't work. Any help would be greatly appreciated!

akrun · Accepted Answer · 2022-01-10 18:35:57Z

0

We may use if_any to check if the 'a1' to 'a15' columns in a row contain the string "2761" - if_any returns a logical vector, which is coerced to binary with + or as.integer to create a new column 'd'

library(dplyr)
df <- df %>%
     mutate(d = +(if_any(matches("^a\\d+$"), ~ . %in% "2761")))

answered Jan 10, 2022 at 18:35

akrun

891k38 gold badges590 silver badges700 bronze badges

Sign up to request clarification or add additional context in comments.

1 Comment

drpringles15 Over a year ago

Wonderful thank you! That's exactly what I wanted.

Mwavu · Accepted Answer · 2022-01-10 20:06:05Z

0

You may use dplyr's rowwise() and c_across() as follows:

df |> 
  rowwise() |> 
  mutate(
    b = grepl(pattern = "2761", x = c_across(a1:a15)) |> any() |> as.numeric()
  )

answered Jan 10, 2022 at 20:06

Mwavu

2,27710 silver badges22 bronze badges

Collectives™ on Stack Overflow

Creating a column based off of multiple columns

2 Answers 2

1 Comment

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

1 Comment

Comments

Your Answer

Sign up or log in

Post as a guest

Related