Wrangle Data with {dplyr}

{dplyr} verbs help you wrangle, clean, and normalize your data

dplyr function	use for
select()	subset columns
filter()	subset rows
arrange()	sort rows by column variable values
mutate()	Create new, or modify variables
group_by()	use with summarize for subtotals
summarize()	generate column totals and subtotals, etc.
count()	a specialized summarize() function

Examples

First we need to load the {dplyr} package for wrangling and the {readr} package for importing CSV data. In our case, we’ll do that by loading the tidyverse which loads {dplyr}, {readr} and several other helpful packages. Then we need to load our data

library(tidyverse)
brodhead_center <- read_csv("data/brodhead_center.csv")

select()

brodhead_center |> 
  select(name, type)

ABCDEFGHIJ0123456789

name <chr>	type <chr>
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill
Devils Krafthouse	bar and grill

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1-10 of 59 rows

Select columns

filter()

brodhead_center |> 
  filter(menuType == "dessert")

ABCDEFGHIJ0123456789

name <chr>	type <chr>	menuType <chr>	itemType <chr>
Devils Krafthouse	bar and grill	dessert	dessert
Devils Krafthouse	bar and grill	dessert	dessert
Devils Krafthouse	bar and grill	dessert	dessert
Cafe	cafe	dessert	dessert
Cafe	cafe	dessert	dessert
Cafe	cafe	dessert	dessert
Cafe	cafe	dessert	dessert

7 rows | 1-4 of 7 columns

Filter by rows

arrange()

brodhead_center |> 
  arrange(cost)

ABCDEFGHIJ0123456789

name <chr>	type <chr>	menuType <chr>	itemType <chr>
Tandoor	restaurant	appetizer	bread
Tandoor	restaurant	appetizer	bread
Tandoor	restaurant	appetizer	bread
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	side	soup
Tandoor	restaurant	appetizer	appetizer
Tandoor	restaurant	appetizer	appetizer
Tandoor	restaurant	appetizer	appetizer

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1-10 of 59 rows | 1-4 of 7 columns

Arrange rows by the values in a column

mutate()

brodhead_center |> 
  mutate(ratings_high = rating * 2)

ABCDEFGHIJ0123456789

name <chr>	type <chr>	menuType <chr>	itemType <chr>
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	appetizer	snack
Devils Krafthouse	bar and grill	entree	sandwich
Devils Krafthouse	bar and grill	entree	sandwich

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1-10 of 59 rows | 1-4 of 8 columns

Create new variable or modify variable with mutate()

We can also mutate data by groups or categories

brodhead_center |> 
  mutate(avg_item_rating_rest = mean(rating, na.rm = TRUE), 
         .by = name, 
         .after = name)

ABCDEFGHIJ0123456789

name <chr>	avg_item_rating_rest <dbl>	type <chr>
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill
Devils Krafthouse	6.65625	bar and grill

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1-10 of 59 rows | 1-3 of 8 columns

count()

Count values in a group
menuType	n
entree	24
appetizer	23
dessert	7
side	5

brodhead_center |> 
  count(menuType)

ABCDEFGHIJ0123456789

menuType <chr>	n <int>
appetizer	23
dessert	7
entree	24
side	5

4 rows

group_by() & summarise()

Summarise column
Sum_of_cost
412

brodhead_center |> 
  group_by(name) |> 
  summarise(min_cost = min(cost), mean_cost = mean(cost), max_cost = max(cost))

ABCDEFGHIJ0123456789

name <chr>	min_cost <dbl>	mean_cost <dbl>	max_cost <dbl>
Cafe	5	6.500000	8
Devils Krafthouse	4	7.500000	10
Tandoor	2	6.315789	12

3 rows

or

Summarize by groups, without group_by()

brodhead_center |> 
  summarise(min_cost = min(cost), .by = name)

ABCDEFGHIJ0123456789

name <chr>	min_cost <dbl>
Devils Krafthouse	4
Tandoor	2
Cafe	5

3 rows