Renaming values in a dataframe if there is a missing character in R

I have a dataframe:

example <- data.frame(
  Event = c('Negative_other 6',
            'Negative_other_7',
            'Neutral_self_1',
            'Negative_other_6',
            'Neutral_self 1',
            'Negative_other_7'),
  Type = c(1,2,2,1,2,2)
)

Some of the values in Event are inconsistently labelled. For example, 'Negative_other_6' and 'Neutral_self_1' sometimes has an underscore between 'other' and the number but sometimes not. Some other values are consistently labelled, like 'Negative_other_7' always has an underscore between 'other' and the number.

I want to update all the values in Event such that there is always an underscore between other and the number.

This is the desired output:

solution <- data.frame(
  Event = c('Negative_other_6',
            'Negative_other_7',
            'Neutral_self_1',
            'Negative_other_6',
            'Neutral_self_1',
            'Negative_other_7'),
  Type = c(1,2,2,1,2,2)
)

Does anyone know an efficient way to do this?

Thank you!

You can use chatr (character translate from ' ' to _

transform(example, Event = chartr(" ", "_", Event))

             Event Type
1 Negative_other_6    1
2 Negative_other_7    2
3   Neutral_self_1    2
4 Negative_other_6    1
5   Neutral_self_1    2
6 Negative_other_7    2

or even gsub for substituting ' ' to _

transform(example, Event = gsub(" ", "_", Event))

             Event Type
1 Negative_other_6    1
2 Negative_other_7    2
3   Neutral_self_1    2
4 Negative_other_6    1
5   Neutral_self_1    2
6 Negative_other_7    2

Using tidyverse:

library(dplyr)
example %>%
  mutate(Event = janitor::make_clean_names(Event))
               Event Type
1   negative_other_6    1
2   negative_other_7    2
3     neutral_self_1    2
4 negative_other_6_2    1
5   neutral_self_1_2    2
6 negative_other_7_2    2