We wish to carry out multiple data transformation operations on the same data frame.
df_2 = df %>%
mutate(
col_4 = !col_3,
col_5 = abs(col_2),
col_6 = round(col_1, 2),
col_7 = col_5 / col_6
)
Here is how this works:
mutate()
. To do so, we pass
to mutate()
multiple data transformation expressions, such as those covered
in Common Transformation Scenarios,
separated by commas.col_4 = !col_3
where we use the logical complement operator !
to create a new
column col_4
that is the logical complement of column col_3
which is of a logical data
type, i.e. it can take the values TRUE
or FALSE
.col_5 = abs(col_2)
where we create a new column col_5
whose values are the absolute values
of the corresponding values of the numeric column col_1
.col_6 = round(col_1, 2)
where we create a new column col_6
whose values are the rounding
to 2 decimal places of the corresponding values of the numeric column col_2
.col_7 = col_5 / col_6
where we create a new column col_7
whose values are the ratio of the
two columns col_5
and col_6
.mutate()
statement as inputs to data
transformation expressions which we do here in col_7 = col_5 / col_6
.mutate()
function. If an existing column is overwritten, it’s
position is not changed.