You can use the following basic syntax to add a column to a data frame in R based on the values in other columns:

#add new column 'col3' with values based on columns 1 and 2
df$col3 <- with(df, ifelse(col1 > col2, value_if_true, value_if_false))

The following examples show how to use this syntax in practice.

Example 1: Add Character Column Based on Other Columns

The following code shows how to add a new character column based on the values in other columns of the data frame:

#create data frame
df <- data.frame(team=c('Mavs', 'Cavs', 'Spurs', 'Nets'),
                 scored=c(99, 90, 84, 96),
                 allowed=c(95, 80, 87, 95))

#view data frame
df

   team scored allowed
1  Mavs     99      95
2  Cavs     90      80
3 Spurs     84      87
4  Nets     96      95

#add 'result' column based on values in 'scored' and 'allowed' columns
df$result <- with(df, ifelse(scored > allowed, 'Win', 'Loss'))

#view updated data frame
df

   team scored allowed result
1  Mavs     99      95    Win
2  Cavs     90      80    Win
3 Spurs     84      87   Loss
4  Nets     96      95    Win

And the following code shows how to add a new character column that combines two ifelse() functions to produce three potential values in a new column:

#create data frame
df <- data.frame(team=c('Mavs', 'Cavs', 'Spurs', 'Nets'),
                 scored=c(99, 90, 84, 96),
                 allowed=c(95, 80, 87, 95))

#view data frame
df

   team scored allowed
1  Mavs     99      95
2  Cavs     90      80
3 Spurs     84      87
4  Nets     96      95

#add 'quality' column based on values in 'scored' and 'allowed' columns
df$quality <- with(df, ifelse(scored > 95, 'great',
                         ifelse(scored > 85, 'good', 'bad')))

#view updated data frame
df

   team scored allowed quality
1  Mavs     99      95   great
2  Cavs     90      80    good
3 Spurs     84      87     bad
4  Nets     96      95   great

Example 2: Add Numeric Column Based on Other Columns

The following code shows how to add a new numeric column to a data frame based on the values in other columns:

#create data frame
df <- data.frame(team=c('Mavs', 'Cavs', 'Spurs', 'Nets'),
                 scored=c(99, 90, 84, 96),
                 allowed=c(95, 80, 87, 95))

#view data frame
df

   team scored allowed
1  Mavs     99      95
2  Cavs     90      80
3 Spurs     84      87
4  Nets     96      95

#add 'lower_score' column based on values in 'scored' and 'allowed' columns
df$lower_score <- with(df, ifelse(scored > allowed, allowed, scored))

#view updated data frame
df

   team scored allowed lower_score
1  Mavs     99      95          95
2  Cavs     90      80          80
3 Spurs     84      87          84
4  Nets     96      95          95