dplyr Pipeline Explorer
Build a step-by-step data pipeline and watch the table transform in real time
filter()
select()
mutate()
group_by()
summarize()
arrange()
Pipeline
Reset
+ Add a step
Choose a verb
filter()
keep rows matching a condition
select()
choose which columns to keep
mutate() / case_when()
add or transform a column
group_by() + summarize()
collapse groups into summary rows
arrange()
reorder rows by a column's values
separate()
split one column into two
unite()
combine two columns into one
Column
Operator
== equals
!= not equal
> greater than
>= at least
< less than
<= at most
Value
+ Add second condition
Join with
& AND
| OR
Column
Operator
== equals
!= not equal
> greater than
>= at least
< less than
<= at most
Value
✕ Remove 2nd condition
Columns to keep
Expression preset
body_mass_kg = body_mass_g / 1000
bill_ratio = bill_length_mm / flipper_length_mm
is_large = body_mass_g > 4500
size_cat = case_when( … )
Group by
Calculate
n() — count rows
mean(col)
median(col)
sum(col)
min(col)
max(col)
Of column
Sort by column
Direction
asc ↑
desc ↓
Column to split
Separator character
New col 1 name
New col 2 name
Column 1
Column 2
New column name
Separator
Add
Cancel
Data — penguins
No rows match the current pipeline.
R Code
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