R - Creating a new variable using same condition on many variables

Question

I am quite a beginner in R and I am stuck with this problem:

I have a dataset (data) of 24 columns. Each column is an answer to a question : "Is your xxx hurting"? xxx varies in each column (it can be back, head...) Each column can take 3 values: 1 if it does not hurt, 2 if it hurts a bit, 3 if it pains.

I want to create a new variable (fragile) to count each time a person said it hurted a bit somewhere.

data$fragile <- ifelse(data$var1 ==2 , 1, 0) + ifelse(data$var2 == 2, 1, 0) + ...

But it is quite long so I would like to not do it

I tried doing a loop but I read somewhere that R is not made to do loops (and my loop does not work anyway)

data$fragile <-  for(i in dataset[1:24]){ifelse(i == 2, 1, 0)}

And when I do head(data$fragile), "NULL" appears...

What should I do?

I am sure this question has already been asked several times but I do not find the right keywords.

This could be help you stackoverflow.com/questions/22337394/… In R when you want to create a new variable you can use the function mutate from dplyr. — Earl Mascetti
– Earl Mascetti, Commented Jun 11, 2020 at 13:32

Jan · Accepted Answer · 2020-06-11 13:32:01Z

1

Given the assumption that you columns of interest have the indices 1:24:

data$fragile <- apply( data[1:24], 1, function(x) sum(x==2, na.rm = TRUE) )

If you have the columns in a different order just change the index.

This solution, however, is quite slow compared to rowSums.

edited Jun 11, 2020 at 13:32

answered Jun 11, 2020 at 13:18

Jan

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2 Comments

Emeline Over a year ago

Thank you so much! I saw that many rows of my new variable fragile were removed into missing values because I assume that in at least one of the other variables, they did not answer the question. How can I resolve this matter?

Jan Over a year ago

Both sumand rowSums support an argument na.rm. If you set this to TRUEthe functions will ignore any missing values.

Ronak Shah · Accepted Answer · 2020-06-11 14:26:09Z

1

You can use rowSums :

data$fragile <- +(rowSums(data == 2) > 0)

This will give 1 to fragile column if there is 2 in any of the column for a particular row.

In the new dplyr 1.0.0 we can use rowwise with cur_data().

library(dplyr)
data %>% rowwise() %>% mutate(fragile = +(any(cur_data() == 2)))

edited Jun 11, 2020 at 14:26

answered Jun 11, 2020 at 13:17

Ronak Shah

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1 Comment

Emeline Over a year ago

Thank you so much!

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