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1) I have a data frame named df, how can I include an if statement within the mutate function used within the pipe operator? The following does not work:

df %>%
 mutate_if(myvar == "A", newColumn = oldColumn*3, newColumn = oldColumn)

The variable myvar is not included in the data frame and is a "flag" variable with values either "A" or "B". When "A", would like to create a new column named "newColumn" in the data frame that is three times the old column (named "oldColumn"), otherwise it is identical to the old column.

2) Would like to divide the column named "numbers" with the entry of numbers which has the minimum value in another column named "seconds", as follows:

df$newCol <- df$numbers / df[df$seconds== min(df$seconds),]$numbers

How can I do that with mutate command and "%>%", so that it looks more handy? Nothing that I tried works unfortunately.

Thanks for any answers, J.

J. Doe
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  • It's easier to help you if you include a simple [reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) with sample input and desired output that can be used to test and verify possible solutions. Why are you forcing yourself to use the `%>%` operator? You seem to be trying to adjust control flow which really isn't what that operator is for. `mutate_if` conditionally mutates columns, it doesn't allow you to turn on or off the entire mutate operation. – MrFlick Nov 27 '19 at 15:46

1 Answers1

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If myvar is just a variable floating around in the environmnet, you can use an if else statement within mutate (similar question here)

library(dplyr)
# Generate dataset
df <- tibble(oldColumn = rnorm(100))
# Mutate with if-else conditions
df <- df %>% mutate(newColumn = if(myvar == "A") oldColumn else if(myvar=="B") oldColumn * 3)

If myvar is included as a column in the dataframe then you could can use case_when.

# Generate dataset
df <- tibble(myvar = sample(c("A", "B"), 100, replace = TRUE),
             oldColumn = rnorm(100))

# Create a new column which depends on the value of myvar
df <- df %>%
    mutate(newColumn = case_when(myvar == "A" ~ oldColumn*3,
                                    myvar == "B" ~ oldColumn))

As for question 2, you can use mutate with "." operater which calls the left hand side (i.e. "df") in the right hand side of the function. Then you can filter down to the row with the minimum value of seconds (top_n statement using -1 as argument), and pull out the value for the numbers variable

# Generate data
df <- tibble(numbers = sample(1:60),
             seconds = sample(1:60))
# Do computation
df <- df %>% mutate(newCol = numbers / top_n(.,-1,seconds) %>% pull(numbers))
Rowan Jacques-Hamilton
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