Data Wrangling with dplyr & Pipes (%>%)

Transform datasets using dplyr verbs: filter(), select(), mutate(), group_by(), and the pipe operator %>%.

The Five Core dplyr Verbs

filter(): Pick observations by their values.

select(): Pick variables by their names.

mutate(): Create new variables with functions of existing variables.

summarise(): Collapse many values into a single summary.

group_by(): Perform operations by group categories.

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Which dplyr verb creates new columns based on transformations of existing columns?