Intro to tidyverse operations

Intro to tidyverse operations#

library(tidyverse)

Piping#

Write code in the order its run!

Read left to right instead of inside -> out!

Avoid PEMDAS confusion!

Without pipes
- cool_down(workout(warm_up(person)))
With pipes
- person |> warm_up() |> workout() |> cool_down()

Usually written with line breaks to help with readability:

person |> 
  warm_up() |> 
  workout() |> 
  cool_down()

Use CTRL+SHIFT+M to type the pipe automagically in RStudio (use CMD instead of CTRL on Mac ofc). Once your fingers get used to it, it is more convenient; doesn’t feel like it at first.

How can I find the absolute sum of just the first 6 elements of x? (note: the head() function is a convenient way to get the first 6 elements).

Solve this with and without piping and compare.

x <- c(1, -2, 3, -4, 5, -6, 7, -8, 9, -10)

Without pipes:

# head -> abs -> sum
sum(abs(head(x)))

21

With pipes:

# head -> abs -> sum
x |> 
  head(6) |> 
  abs() |> 
  sum()

21

Data manipulation toolkit#

Functions to know for tidy data manipulation:

Grab certain columns with select()
Filter data.frames with filter()
Sort data.frames with arrange()
- Often paired with desc() for sorting in descending order
Create/modify columns with mutate()
Create summaries with group_by() |> summarise()
- package created by a New Zealander; use z to feel more American
- useful to use n() function to count rows within summarise()

Good to know exist, but less focus for us as we get started:

Join data.frames with:
- inner_join()
- left_join()
- right_join()
- full_join()
Stack data.frames with bind_rows()

Data practice#

Get to know the starwars data.frame

# reset data to original
data("starwars", package = "dplyr")

# summary(starwars) # scares adam v much
summary(starwars$height)
names(starwars)
nrow(starwars)
ncol(starwars)

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
   66.0   167.0   180.0   174.6   191.0   264.0       6 

'name'
'height'
'mass'
'hair_color'
'skin_color'
'eye_color'
'birth_year'
'sex'
'gender'
'homeworld'
'species'
'films'
'vehicles'
'starships'

87

14

Currently height is listed in cm. Create a height_in column showing the height in inches.

starwars <- starwars |> 
  mutate(height_in = height / 2.54)

starwars |>
  select(name, height_in) |>
  arrange(height_in)

A tibble: 87 × 2
name	height_in
<chr>	<dbl>
Yoda	25.98425
Ratts Tyerel	31.10236
Wicket Systri Warrick	34.64567
Dud Bolt	37.00787
R2-D2	37.79528
R4-P17	37.79528
R5-D4	38.18898
Sebulba	44.09449
Gasgano	48.03150
Watto	53.93701
Leia Organa	59.05512
Mon Mothma	59.05512
Cordé	61.81102
Nien Nunb	62.99213
Shmi Skywalker	64.17323
Ben Quadinaros	64.17323
Beru Whitesun Lars	64.96063
Dormé	64.96063
Barriss Offee	65.35433
C-3PO	65.74803
Jocasta Nu	65.74803
Zam Wesell	66.14173
Wedge Antilles	66.92913
Palpatine	66.92913
Finis Valorum	66.92913
Luminara Unduli	66.92913
Eeth Koth	67.32283
Luke Skywalker	67.71654
Greedo	68.11024
Jabba Desilijic Tiure	68.89764
⋮	⋮
Raymus Antilles	74.01575
Bossk	74.80315
Nute Gunray	75.19685
Bail Prestor Organa	75.19685
San Hill	75.19685
Qui-Gon Jinn	75.98425
Dooku	75.98425
Wat Tambor	75.98425
Jar Jar Binks	77.16535
Kit Fisto	77.16535
Mas Amedda	77.16535
Ki-Adi-Mundi	77.95276
Dexter Jettster	77.95276
IG-88	78.74016
Darth Vader	79.52756
Rugor Nass	81.10236
Tion Medon	81.10236
Taun We	83.85827
Grievous	85.03937
Roos Tarpals	88.18898
Chewbacca	89.76378
Lama Su	90.15748
Tarfful	92.12598
Yarael Poof	103.93701
Arvel Crynyd	NA
Finn	NA
Rey	NA
Poe Dameron	NA
BB8	NA
Captain Phasma	NA

This is equivalent to:

starwars$height_in <- starwars$height / 2.54
starwars[ order(starwars$height_in) , c('name', 'height_in') ]

A tibble: 87 × 2
name	height_in
<chr>	<dbl>
Yoda	25.98425
Ratts Tyerel	31.10236
Wicket Systri Warrick	34.64567
Dud Bolt	37.00787
R2-D2	37.79528
R4-P17	37.79528
R5-D4	38.18898
Sebulba	44.09449
Gasgano	48.03150
Watto	53.93701
Leia Organa	59.05512
Mon Mothma	59.05512
Cordé	61.81102
Nien Nunb	62.99213
Shmi Skywalker	64.17323
Ben Quadinaros	64.17323
Beru Whitesun Lars	64.96063
Dormé	64.96063
Barriss Offee	65.35433
C-3PO	65.74803
Jocasta Nu	65.74803
Zam Wesell	66.14173
Wedge Antilles	66.92913
Palpatine	66.92913
Finis Valorum	66.92913
Luminara Unduli	66.92913
Eeth Koth	67.32283
Luke Skywalker	67.71654
Greedo	68.11024
Jabba Desilijic Tiure	68.89764
⋮	⋮
Raymus Antilles	74.01575
Bossk	74.80315
Nute Gunray	75.19685
Bail Prestor Organa	75.19685
San Hill	75.19685
Qui-Gon Jinn	75.98425
Dooku	75.98425
Wat Tambor	75.98425
Jar Jar Binks	77.16535
Kit Fisto	77.16535
Mas Amedda	77.16535
Ki-Adi-Mundi	77.95276
Dexter Jettster	77.95276
IG-88	78.74016
Darth Vader	79.52756
Rugor Nass	81.10236
Tion Medon	81.10236
Taun We	83.85827
Grievous	85.03937
Roos Tarpals	88.18898
Chewbacca	89.76378
Lama Su	90.15748
Tarfful	92.12598
Yarael Poof	103.93701
Arvel Crynyd	NA
Finn	NA
Rey	NA
Poe Dameron	NA
BB8	NA
Captain Phasma	NA

Filter to all the characters under 4 ft tall.

starwars |> 
  filter(height_in < 4 * 12) |> 
  select(name, height_in) |> 
  arrange(height_in)

A tibble: 8 × 2
name	height_in
<chr>	<dbl>
Yoda	25.98425
Ratts Tyerel	31.10236
Wicket Systri Warrick	34.64567
Dud Bolt	37.00787
R2-D2	37.79528
R4-P17	37.79528
R5-D4	38.18898
Sebulba	44.09449

This is equivalent to:

starwars_sub <- starwars
starwars_sub <- subset(starwars_sub, height_in < 4*12)
starwars_sub <- starwars_sub[ order(starwars_sub$height_in) , ]
starwars_sub[ , c('name', 'height_in') ]

A tibble: 8 × 2
name	height_in
<chr>	<dbl>
Yoda	25.98425
Ratts Tyerel	31.10236
Wicket Systri Warrick	34.64567
Dud Bolt	37.00787
R2-D2	37.79528
R4-P17	37.79528
R5-D4	38.18898
Sebulba	44.09449

Show the top 5 tallest characters.

starwars |>
  arrange(desc(height_in)) |> 
  select(name, height_in) |> 
  head(5)

A tibble: 5 × 2
name	height_in
<chr>	<dbl>
Yarael Poof	103.93701
Tarfful	92.12598
Lama Su	90.15748
Chewbacca	89.76378
Roos Tarpals	88.18898

This is equivalent to:

starwars[ order(starwars$height_in, decreasing=TRUE)[1:5] , c('name', 'height_in') ]

A tibble: 5 × 2
name	height_in
<chr>	<dbl>
Yarael Poof	103.93701
Tarfful	92.12598
Lama Su	90.15748
Chewbacca	89.76378
Roos Tarpals	88.18898

Show the top 5 tallest humans

starwars |> 
  filter(species == "Human") |> 
  arrange(desc(height_in)) |> 
  select(name, height_in) |> 
  head(5)

A tibble: 5 × 2
name	height_in
<chr>	<dbl>
Darth Vader	79.52756
Qui-Gon Jinn	75.98425
Dooku	75.98425
Bail Prestor Organa	75.19685
Anakin Skywalker	74.01575

This is equivalent to:

starwars_sub <- starwars
starwars_sub <- subset(starwars_sub, species=='Human')
starwars_sub <- starwars_sub[ order(starwars_sub$height, decreasing=TRUE) , ]
starwars_sub[ 1:5 , c('name', 'height_in') ]

A tibble: 5 × 2
name	height_in
<chr>	<dbl>
Darth Vader	79.52756
Qui-Gon Jinn	75.98425
Dooku	75.98425
Bail Prestor Organa	75.19685
Anakin Skywalker	74.01575

Show the average mass by species (this is in kilograms).

starwars |> 
  group_by(species) |>
  summarise(
    avg_mass = mean(mass, na.rm = TRUE),
    n = n()
  )

A tibble: 38 × 3
species	avg_mass	n
<chr>	<dbl>	<int>
Aleena	15.00	1
Besalisk	102.00	1
Cerean	82.00	1
Chagrian	NaN	1
Clawdite	55.00	1
Droid	69.75	6
Dug	40.00	1
Ewok	20.00	1
Geonosian	80.00	1
Gungan	74.00	3
Human	81.31	35
Hutt	1358.00	1
Iktotchi	NaN	1
Kaleesh	159.00	1
Kaminoan	88.00	2
Kel Dor	80.00	1
Mirialan	53.10	2
Mon Calamari	83.00	1
Muun	NaN	1
Nautolan	87.00	1
Neimodian	90.00	1
Pau'an	80.00	1
Quermian	NaN	1
Rodian	74.00	1
Skakoan	48.00	1
Sullustan	68.00	1
Tholothian	50.00	1
Togruta	57.00	1
Toong	65.00	1
Toydarian	NaN	1
Trandoshan	113.00	1
Twi'lek	55.00	2
Vulptereen	45.00	1
Wookiee	124.00	2
Xexto	NaN	1
Yoda's species	17.00	1
Zabrak	80.00	2
NA	81.00	4

Important

Please write the eqivalent code with R loops, conditions, and/or functions.

Intro to tidyverse operations

Contents

Intro to tidyverse operations#

Piping#

Data manipulation toolkit#

Data practice#