Themes from scratch IN TR OD U C TION TO DATA VISU AL IZATION W - - PowerPoint PPT Presentation

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Themes from scratch IN TR OD U C TION TO DATA VISU AL IZATION W - - PowerPoint PPT Presentation

Sep 07, 2022 275 likes •825 views

Themes from scratch IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT 2 Rick Sca v e a Fo u nder , Sca v e a Academ y The themes la y er All non - data ink Vis u al elements not part of the data INTRODUCTION TO DATA

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Themes from scratch

IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT2

Rick Scavea

Founder, Scavea Academy

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

The themes layer

All non-data ink Visual elements not part of the data

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

The themes layer

All non-data ink Visual elements not part of the data Three types type text line rectangle

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

The themes layer

All non-data ink Visual elements not part of the data Three types type modied using text element_text() line element_line() rectangle element_rect()

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

A starting plot...

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) + geom_jitter(alpha = 0.6)

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

The text elements

text axis.title axis.title.x axis.title.x.top axis.title.x.bottom axis.title.y axis.title.y.left axis.title.y.right title legend.title plot.title plot.subtitle plot.caption plot.tag axis.text axis.text.x axis.text.x.top axis.text.x.bottom axis.text.y axis.text.y.left axis.text.y.right legend.text strip.text strip.text.x strip.text.y

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

The text elements

theme( text, axis.title, axis.title.x, axis.title.x.top, axis.title.x.bottom, axis.title.y, axis.title.y.left, axis.title.y.right, title, legend.title, plot.title, plot.subtitle, plot.caption, plot.tag, axis.text, axis.text.x, axis.text.x.top, axis.text.x.bottom, axis.text.y, axis.text.y.left, axis.text.y.right, legend.text, strip.text, strip.text.x, strip.text.y)

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Adjusting theme elements

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) + geom_jitter(alpha = 0.6) + theme(axis.title = element_text(color = "blue"))

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

A starting plot...

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) + geom_jitter(alpha = 0.6)

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Line elements

theme( line, axis.ticks, axis.ticks.x, axis.ticks.x.top, axis.ticks.x.bottom, axis.ticks.y, axis.ticks.y.left, axis.ticks.y.right, axis.line, axis.line.x, axis.line.x.top, axis.line.x.bottom, axis.line.y, axis.line.y.left, axis.line.y.right, panel.grid, panel.grid.major, panel.grid.major.x, panel.grid.major.y, panel.grid.minor, panel.grid.minor.x, panel.grid.minor.y)

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

A starting plot...

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) + geom_jitter(alpha = 0.6)

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Rect elements

theme( rect, legend.background, legend.key, legend.box.background, panel.background, panel.border, plot.background, strip.background, strip.background.x, strip.background.y)

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Hierarchical naming reflects inheritance rules

e.g. Text

text axis.title axis.title.x axis.title.x.top axis.title.x.bottom axis.title.y axis.title.y.left axis.title.y.right

e.g. Lines

line axis.ticks axis.ticks.x axis.ticks.x.top axis.ticks.x.bottom axis.ticks.y axis.ticks.y.left, axis.ticks.y.right axis.line axis.line.x axis.line.x.top axis.line.x.bottom axis.line.y axis.line.y.left axis.line.y.right

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

element_blank()

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) + geom_jitter(alpha = 0.6) + theme(line = element_blank(), rect = element_blank(), text = element_blank())

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Let's practice!

IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT2

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Theme flexibility

IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT2

Rick Scavea

Founder, Scavea Academy

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Ways to use themes

  • 1. From scratch (last video)
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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Ways to use themes

  • 1. From scratch (last video)
  • 2. Theme layer object
  • 3. Built-in themes

ggplot2 or ggthemes packages

  • 4. Built-in themes from other packages
  • 5. Update/Set default theme
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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Defining theme objects

Useful when you have many plots Provides consistency in style Apply a specic theme everywhere

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Defining theme objects

z <- ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) + geom_jitter(alpha = 0.6) + scale_x_continuous("Sepal Length (cm)", limits = c(4,8), expand = c(0,0)) + scale_y_continuous("Sepal Width (cm)", limits = c(1.5,5), expand = c(0,0)) + scale_color_brewer("Species", palette = "Dark2", labels = c("Setosa", "Versicolor", "Virginica"))

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Defining theme objects

z + theme(text = element_text(family = "serif", size = 14), rect = element_blank(), panel.grid = element_blank(), title = element_text(color = "#8b0000"), axis.line = element_line(color = "black"))

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Defining theme objects

theme_iris <- theme(text = element_text(family = "serif", size = 14), rect = element_blank(), panel.grid = element_blank(), title = element_text(color = "#8b0000"), axis.line = element_line(color = "black"))

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Reusing theme objects

z + theme_iris

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Reusing theme objects

m <- ggplot(iris, aes(x = Sepal.Width)) + geom_histogram(binwidth = 0.1, center = 0.05) m

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Reusing theme objects

m + theme_iris

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Reusing theme objects

m + theme_iris + theme(axis.line.x = element_blank())

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Ways to use themes

  • 1. From scratch (last video)
  • 2. Theme layer object
  • 3. Built-in themes

ggplot2 or ggthemes packages

  • 4. Built-in themes from other packages
  • 5. Update/Set default theme
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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Using built-in themes

Use theme_*() functions to access built-in themes.

z + theme_classic()

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Using built-in themes

Use theme_*() functions to access built-in themes.

z + theme_classic() + theme(text = element_text(family = "serif"))

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Ways to use themes

  • 1. From scratch (last video)
  • 2. Theme layer object
  • 3. Built-in themes

ggplot2 or ggthemes packages

  • 4. Built-in themes from other packages
  • 5. Update/Set default theme
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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

The ggthemes package

Use the ggthemes package for more functions.

library(ggthemes) z + theme_tufte()

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Ways to use themes

  • 1. From scratch (last video)
  • 2. Theme layer object
  • 3. Built-in themes

ggplot2 or ggthemes packages

  • 4. Built-in themes from other packages
  • 5. Update/Set default theme
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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Updating themes

  • riginal <- theme_update(text = element_text(family = "serif", size = 14),

rect = element_blank(), panel.grid = element_blank(), title = element_text(color = "#8b0000"), axis.line = element_line(color = "black"))

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Updating themes

z

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Setting themes

theme_set(original) # Alternatively # theme_set(theme_grey())

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Let's practice!

IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT2

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Effective explanatory plots

IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT2

Rick Scavea

Founder, Scavea Academy

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Our goal, an effective explanatory plot

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Complete data

dplyr::glimpse(gm2007_full) Observations: 142 Variables: 3 $ country <fct> "Afghanistan", "Albania", "Algeria", "Angola", "Argentina", "Au... $ lifeExp <dbl> 43.828, 76.423, 72.301, 42.731, 75.320, 81.235, 79.829, 75.635,... $ continent <fct> Asia, Europe, Africa, Africa, Americas, Oceania, Europe, Asia, ...

We would begin with our complete data set, which contains three variables for 142 countries.

1

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

First exploratory plots - distributions

ggplot(gm2007_full, aes(lifeExp)) + geom_histogram()

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

First exploratory plots - distributions

ggplot(gm2007_full_arranged, aes(index, lifeExp)) + geom_point()

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

First exploratory plots - distributions

ggplot(gm2007_full_arranged, aes(index, lifeExp, col = continent)) + geom_point()

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Our data

dplyr::glimpse(gm2007) Observations: 20 Variables: 3 $ country <fct> "Swaziland", "Mozambique", "Zambia", "Sierra Leone", "Lesotho... $ lifeExp <dbl> 39.613, 42.082, 42.384, 42.568, 42.592, 42.731, 43.487, 43.82... $ continent <fct> Africa, Africa, Africa, Africa, Africa, Africa, Africa, Asia,... >

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

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Use intuitive and attractive geoms

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INTRODUCTION TO DATA VISUALIZATION WITH GGPLOT2

Add text labels to your plot

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Use appropriate scales

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Add useful titles and citations

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Remove non-data ink

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Add threshold lines

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Add informative text

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Add embellishments

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Let's practice!

IN TR OD U C TION TO DATA VISU AL IZATION W ITH G G P L OT2