DATA
VISUALIZATION

Dr. Ajay Kumar Koli, PhD | SARA Institute of Data Science, India

“The simple graph has brought more information to the data analyst’s mind than any other device.” — John Tukey

Goal

How to visualize data using R package ggplot2.

Source: Tanya Shapiro

ggplot2 Layers

Import Data

• Task
• Code
• Output

library(tidyverse)
library(palmerpenguins)

ggplot(data = penguins)

Figure 1

Map Variables Aesthetics

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = species))

Figure 2

Add Geometric Shapes

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = species)) +
  geom_bar()

Figure 3

Key Components are:

1. data,

2. A set of aesthetic mappings between variables in the data and visual properties, and

3. At least one layer which describes how to render each observation. Layers are usually created with a geom function.

🧠 YOUR TURN

• Task
• Answer

ggplot(data = penguins,
       mapping = aes(x = island)) +
  geom_bar()

05:00

Common Mistakes

• Make sure that every ( is matched with a ) and every " is paired with another ".

• Console shows no results but a + sign that means your code is incomplete and R is waiting for you to complete the code.

• in ggplot + has to come at the end of the line, not the start

“Fill” Color

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = species)) +
  geom_bar(fill = "blue")

Figure 4

“Fill” Colors

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = species)) +
  geom_bar(fill = c("blue", "green", "yellow"))

Figure 5

“Fill” & “Color” Colors

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = species)) +
  geom_bar(fill = c("blue", "green", "yellow"),
           color = "black")

Figure 6

🧠 YOUR TURN

• Task
• Answer

ggplot(data = penguins,
       mapping = aes(x = island)) +
  geom_bar(fill = c("red", "yellow", "darkgreen"),
           color = "black")

05:00

Know Your Data

glimpse(penguins)

Rows: 344
Columns: 8
$ species           <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel…
$ island            <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse…
$ bill_length_mm    <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, …
$ bill_depth_mm     <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, …
$ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186…
$ body_mass_g       <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, …
$ sex               <fct> male, female, female, NA, female, male, female, male…
$ year              <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…

Plot A Continuous Variable

• Task
• Code
• Output

# bill_length_mm is dbl type variable/column

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm)) +
  geom_histogram()

Figure 7

🧠 YOUR TURN

• Task
• Answer

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm)) +
  geom_histogram(fill = "darkblue",
                 color = "white")

05:00

Two Continuous Variables

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point()

Figure 8

Geom Size

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(size = 5)

Figure 9

Geom Shape

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(size = 5,
             shape = 8)

Figure 10

🧠 YOUR TURN

• Task
• Answer

ggplot(data = penguins,
       mapping = aes(x = body_mass_g, y = flipper_length_mm)) +
  geom_point(size = 2, shape = 23, color = "red", fill = "gold")

05:00

Plot A Factor & Factor

• Task
• Code
• Output

Sometimes, we want to differentiate values of a factor/category variable on the basis of another factor/category variable.

ggplot(data = penguins,
       mapping = aes(x = island)) +
  geom_bar(aes(fill = sex))

Figure 11

Plot A Factor & Continuous

• Task
• Code
• Output

Sometimes, we want to differentiate values from a continuous variable on the basis of factor/category variables.

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm)) +
  geom_histogram(aes(fill = sex), color = "black")

Figure 12

A Factor & Two Cont.

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = sex))

Figure 13

A Factor & Two Cont.

• Task
• Code
• Output

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species))

Figure 14

Write Labels

• Task
• Code
• Output

• Title of the plot

• Subtitle of the plot with more information

• Title of the x-axis

• Title of the y-axis

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  )

Figure 15

Different Shapes

• Task
• Code
• Output

Each level of the factor/category can be shown using a different shape of different color.

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  )

Figure 16

Various Themes

• Task
• Code
• Output

Source: ggthemes

library(ggthemes)

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_economist()

Figure 17

Various Themes

• Task
• Code
• Output

Source: ggthemes

library(ggthemes)

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_solarized_2()

Figure 18

Various Themes

• Task
• Code
• Output

Source: ggthemes

library(ggthemes)

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_tufte()

Figure 19

Various Themes

• Task
• Code
• Output

Source: ggthemes

library(ggthemes)

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_clean()

Figure 20

Color Palette

Color Palette

• Task
• Code
• Output

R package ggthemes have function to use color scheme for colorblindness. Know more

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_clean() +
  scale_color_colorblind()

Figure 21

Color Palette

• Task
• Code
• Output

library(RColorBrewer)

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_clean() +
  scale_color_brewer(palette = "Dark2")

Figure 22

Color Palette

• Task
• Code
• Output

library(wesanderson)

names(wes_palettes)

 [1] "BottleRocket1"     "BottleRocket2"     "Rushmore1"        
 [4] "Rushmore"          "Royal1"            "Royal2"           
 [7] "Zissou1"           "Zissou1Continuous" "Darjeeling1"      
[10] "Darjeeling2"       "Chevalier1"        "FantasticFox1"    
[13] "Moonrise1"         "Moonrise2"         "Moonrise3"        
[16] "Cavalcanti1"       "GrandBudapest1"    "GrandBudapest2"   
[19] "IsleofDogs1"       "IsleofDogs2"       "FrenchDispatch"   
[22] "AsteroidCity1"     "AsteroidCity2"     "AsteroidCity3"    

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_clean() +
  scale_color_manual(values = wes_palette("BottleRocket2", n = 3))

Figure 23

Export Plot

• Task
• Code
• Output

Export/save plot as pdf, jpg or png file.

ggplot(data = penguins,
       mapping = aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species, shape = species)) +
  labs(
    title = "The title of the plot",
    subtitle = "The subtitle of the plot",
    x = "Bill length (mm)",
    y = "Bill depth (mm)"
  ) +
  theme_clean() +
  scale_color_manual(values = wes_palette("BottleRocket2", n = 3))

ggsave("penguins-plot.pdf")

Figure 24

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