ggplot2 in R

Author

Tony Duan

Code

library(tidyverse)
library(gapminder)
library(ggpubr)
library(ggthemr)

library(ggplot2)
library(plotly)

library(magick)
packageVersion("ggplot2")

[1] '3.5.1'

Code

library(reshape2)
tips=tips
head(tips)

  total_bill  tip    sex smoker day   time size
1      16.99 1.01 Female     No Sun Dinner    2
2      10.34 1.66   Male     No Sun Dinner    3
3      21.01 3.50   Male     No Sun Dinner    3
4      23.68 3.31   Male     No Sun Dinner    2
5      24.59 3.61 Female     No Sun Dinner    4
6      25.29 4.71   Male     No Sun Dinner    4

Code

data001=gapminder
head(data001)

# A tibble: 6 × 6
  country     continent  year lifeExp      pop gdpPercap
  <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
1 Afghanistan Asia       1952    28.8  8425333      779.
2 Afghanistan Asia       1957    30.3  9240934      821.
3 Afghanistan Asia       1962    32.0 10267083      853.
4 Afghanistan Asia       1967    34.0 11537966      836.
5 Afghanistan Asia       1972    36.1 13079460      740.
6 Afghanistan Asia       1977    38.4 14880372      786.

1 Scatter Plot

Code

p=ggplot(tips, aes(tip, total_bill)) + geom_point()
p

1.1 color by group

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()
p

1.2 size by group

Code

p=ggplot(tips, aes(tip, total_bill,colour = sex,size=size)) + geom_point()
p

1.3 line Plot

Code

data002= data001 %>% group_by(continent,year) %>% summarise(pop=sum(pop))

Code

p=ggplot(data002 %>%filter(continent=='Asia'), aes(year, pop)) + geom_line()
p

1.3.1 change line size

Code

p=ggplot(data002 %>%filter(continent=='Asia'), aes(year, pop)) + geom_line(size=5)
p

1.4 color by group

Code

p=ggplot(data002, aes(year, pop,colour = continent)) + geom_line()
p

2 histogram

Code

data002= data001 %>% filter(year==1997,continent %in% c('Asia','Africa'))

Code

ggplot(data002, aes(gdpPercap)) + 
  geom_histogram()

2.1 color by group

Code

ggplot(data002, aes(gdpPercap,,fill = continent)) +geom_histogram(position = 'dodge')

3 bar chart

Code

data002= data001 %>% filter(year==1997) %>% group_by(continent) %>% summarise(pop=sum(pop))

Code

ggplot(data002, aes(x=continent, y=pop)) +
  geom_bar(stat="identity")+scale_y_continuous(labels = scales::comma)

3.1 show number

Code

ggplot(data002, aes(x=continent, y=pop)) +
  geom_bar(stat="identity")+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2)

3.2 change bar color

Code

ggplot(data002, aes(x=continent, y=pop)) +
  geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2)

Code

# box plot

3.3 bar plot order

Code

ggplot(data002, aes(x=reorder(continent,pop), y=pop)) +
  geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2)

Code

# box plot

Code

ggplot(data002, aes(x=reorder(continent,-pop), y=pop)) +
  geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2)

Code

# box plot

3.4 Horizontal Barplot

` ::: {.cell}

Code

ggplot(data002, aes(x=reorder(continent,pop), y=pop)) +
  geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2)+coord_flip()

Code

# box plot

:::

3.5 make bar transparency

Code

ggplot(data002, aes(x=reorder(continent,pop), y=pop)) +
  geom_bar(stat="identity",fill='red' ,alpha=0.2)+coord_flip()

3.6 make bar close to axis

Code

ggplot(data002, aes(x=reorder(continent,pop), y=pop)) +
  geom_bar(stat="identity",alpha=0.2,fill='red')+coord_flip()+scale_y_continuous(expand = expansion(mult = c(0, .1)))

3.7 change one bar color

Code

ggplot(data002, aes(x=reorder(continent,pop), y=pop,fill=factor(ifelse(continent=="Asia","Highlighted","Normal")))) +
  geom_bar(stat="identity",alpha=0.2,show.legend = FALSE)+scale_fill_manual(name = "continent", values=c("red","grey50"))+coord_flip()+scale_y_continuous(expand = expansion(mult = c(0, .1)))

3.8 color by group

4 box plot

Code

p=ggplot(tips, aes(day,tip,fill=sex)) + geom_boxplot()
p

5 strip plot

Code

p=ggplot(tips, aes(day,tip)) + geom_jitter()
p

5.1 color by group

Code

p=ggplot(tips, aes(day,tip,color=sex)) + geom_jitter(position=position_jitterdodge())
p

6 Facet plot

Code

p=ggplot(tips, aes(tip,total_bill,)) + geom_point(aes(color=sex)) + facet_wrap("day")
p

make 3 plot per row

Code

p=ggplot(tips, aes(tip,total_bill,)) + geom_point(aes(color=sex)) + facet_wrap("day",ncol = 3)
p

7 title,size,x y name,footnote

7.1 add title

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")
p

7.2 add subtitle

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex",subtitle = "Subtitle of the plot")
p

7.3 add footnote

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")+labs(caption = "this is footnote")
p

7.4 adjust plot size

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")+theme(
  plot.margin = margin(2, 2, 5, 5, "cm"))
p

7.5 adjust text size and center title

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")+labs(caption = "this is footnote")

p+theme(plot.title = element_text(hjust = 0.5),text = element_text(size = 30))

7.6 change x y name

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+xlab("new x name") + ylab("new y name")
p

7.7 add chinese

Code

library(showtext)
showtext_auto()

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="新的 x name")+ scale_y_continuous(name="新的 y name")
p

7.8 x y break and scales limit

7.8.1 x scales limit

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")
p+ xlim(min=0, 20)

7.8.2 y scales limit

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")
p+ ylim(0, 100)

7.8.3 adding second aix

Code

data002= data001%>% group_by(year,continent) %>% summarise(pop=sum(pop),lifeExp=mean(lifeExp))%>%filter(continent=='Asia')

remove scientific notation ::: {.cell}

Code

coeff=1/40000000


p=ggplot(data002, aes(year, pop)) + geom_col() +
  geom_line(aes(year,lifeExp/ coeff),size=2, color = "red") +scale_y_continuous("pop", sec.axis = sec_axis(~.*coeff, name = "lifeExp"),labels = scales::comma)
p

:::

8 applying themes

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")
p+ theme_bw()

Code

p+ theme_light()

Code

library("ggthemes")
p+ theme_economist()

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")
p+ theme_tufte()

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")
p+ theme_wsj()

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")
p+ theme_fivethirtyeight()

9 convert ggplot to plotly

Code

p=ggplot(data=tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")

pp=ggplotly(p)

pp

10 Save plot

Code

p+ theme_economist()

Code

ggsave("myplot.png")

11 add image into the chart

11.1 add logo

Code

# Add your company's logo to the graph you created
logo <- image_read("logo.png")
p
grid::grid.raster(logo, x = 0.1, y = 0, just = c('left', 'bottom'), width = unit(0.4, 'inches'))

11.2 add background image

Code

img4=image_read("bee.png")

"bee.png"

[1] "bee.png"

Code

p=ggplot(tips, aes(tip, total_bill,color=sex)) + background_image(img4) +geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name")


p

12 Animation plot

Code

#pak::pak('thomasp85/gganimate')
library(gganimate)


p=ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7, show.legend = FALSE) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  # Here comes the gganimate specific bits
  # labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy',colour = "country") +
  labs(title ='Year: {as.integer(frame_time)}', x = 'GDP per capita', y = 'life expectancy',colour = "country") +
  transition_time(year) +
  ease_aes('linear')

p

13 ggplot2 extension packages

https://www.youtube.com/watch?v=efj6-aawubs&list=PLBnFxG6owe1FcJnrNbaIJyALHMyoKW27T

13.1 patchwork

The goal of patchwork is to make it ridiculously simple to combine separate ggplots into the same graphic.

Code

#pak::pak('patchwork')

Code

library(ggplot2)
library(patchwork)

p1 <- ggplot(mtcars) + geom_point(aes(mpg, disp))
p2 <- ggplot(mtcars) + geom_boxplot(aes(gear, disp, group = gear))

p3 <- ggplot(mtcars) + geom_smooth(aes(disp, qsec))
p4 <- ggplot(mtcars) + geom_bar(aes(carb))

(p1 | p2 | p3) /
      p4

13.2 legendry

The goal of legendry is to provide additional guide functionality to the ggplot2 ecosystem.

Code

#pak::pak('legendry')

Code

library(ggplot2)
library(legendry)

Code

base <- ggplot(mpg, aes(displ, hwy, colour = cty)) +
  geom_point() +
  labs(
    x = "Engine displacement",
    y = "Highway miles per gallon",
    col = "City miles\nper gallon"
  ) +
  theme(axis.line = element_line())

Code

# A partial guide to display a bracket
efficient_bracket <- primitive_bracket(
  # Keys determine what is displayed
  key = key_range_manual(start = 25, end = Inf, name = "Efficient"),
  bracket = "square",
  # We want vertical text
  theme = theme(
    legend.text = element_text(angle = 90, hjust = 0.5),
    axis.text.y.left = element_text(angle = 90, hjust = 0.5)
  )
)

base + guides(y = guide_axis_stack("axis", efficient_bracket))

13.3 marquee

13.4 ggiraph

13.5 geomtextpath

13.6 ggpattern

13.7 ggbump

13.8 gghighlight

13.9 ggdist

14 reference:

https://cran.r-project.org/web/packages/magick/vignettes/intro.html

https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/

--- title: "ggplot2 in R" author: "Tony Duan" execute: warning: false error: false format: html: toc: true toc-location: right code-fold: show code-tools: true number-sections: true code-block-bg: true code-block-border-left: "#31BAE9" code-copy: true --- ![](images/Screenshot 2023-07-08 at 5.03.46 PM.png){width="800"} ```{r} library(tidyverse) library(gapminder) library(ggpubr) library(ggthemr) library(ggplot2) library(plotly) library(magick) packageVersion("ggplot2") ``` ```{r} library(reshape2) tips=tips head(tips) ``` ```{r} data001=gapminder head(data001) ``` # Scatter Plot ```{r} p=ggplot(tips, aes(tip, total_bill)) + geom_point() p ``` ## color by group ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point() p ``` ## size by group ```{r} p=ggplot(tips, aes(tip, total_bill,colour = sex,size=size)) + geom_point() p ``` ## line Plot ```{r} data002= data001 %>% group_by(continent,year) %>% summarise(pop=sum(pop)) ``` ```{r} p=ggplot(data002 %>%filter(continent=='Asia'), aes(year, pop)) + geom_line() p ``` ### change line size ```{r} p=ggplot(data002 %>%filter(continent=='Asia'), aes(year, pop)) + geom_line(size=5) p ``` ## color by group ```{r} p=ggplot(data002, aes(year, pop,colour = continent)) + geom_line() p ``` # histogram ```{r} data002= data001 %>% filter(year==1997,continent %in% c('Asia','Africa')) ``` ```{r} ggplot(data002, aes(gdpPercap)) + geom_histogram() ``` ## color by group ```{r} ggplot(data002, aes(gdpPercap,,fill = continent)) +geom_histogram(position = 'dodge') ``` # bar chart ```{r} data002= data001 %>% filter(year==1997) %>% group_by(continent) %>% summarise(pop=sum(pop)) ``` ```{r} ggplot(data002, aes(x=continent, y=pop)) + geom_bar(stat="identity")+scale_y_continuous(labels = scales::comma) ``` ## show number ```{r} ggplot(data002, aes(x=continent, y=pop)) + geom_bar(stat="identity")+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2) ``` ## change bar color ```{r} ggplot(data002, aes(x=continent, y=pop)) + geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2) # box plot ``` ## bar plot order ```{r} ggplot(data002, aes(x=reorder(continent,pop), y=pop)) + geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2) # box plot ``` ```{r} ggplot(data002, aes(x=reorder(continent,-pop), y=pop)) + geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2) # box plot ``` ## Horizontal Barplot ` ```{r} ggplot(data002, aes(x=reorder(continent,pop), y=pop)) + geom_bar(stat="identity",fill='red')+scale_y_continuous(labels = scales::comma)+geom_text(aes(label = pop), vjust = -0.2)+coord_flip() # box plot ``` ## make bar transparency ```{r} ggplot(data002, aes(x=reorder(continent,pop), y=pop)) + geom_bar(stat="identity",fill='red' ,alpha=0.2)+coord_flip() ``` ## make bar close to axis ```{r} ggplot(data002, aes(x=reorder(continent,pop), y=pop)) + geom_bar(stat="identity",alpha=0.2,fill='red')+coord_flip()+scale_y_continuous(expand = expansion(mult = c(0, .1))) ``` ## change one bar color ```{r} ggplot(data002, aes(x=reorder(continent,pop), y=pop,fill=factor(ifelse(continent=="Asia","Highlighted","Normal")))) + geom_bar(stat="identity",alpha=0.2,show.legend = FALSE)+scale_fill_manual(name = "continent", values=c("red","grey50"))+coord_flip()+scale_y_continuous(expand = expansion(mult = c(0, .1))) ``` ## color by group # box plot ```{r} p=ggplot(tips, aes(day,tip,fill=sex)) + geom_boxplot() p ``` # strip plot ```{r} p=ggplot(tips, aes(day,tip)) + geom_jitter() p ``` ## color by group ```{r} p=ggplot(tips, aes(day,tip,color=sex)) + geom_jitter(position=position_jitterdodge()) p ``` # Facet plot ```{r} p=ggplot(tips, aes(tip,total_bill,)) + geom_point(aes(color=sex)) + facet_wrap("day") p ``` make 3 plot per row ```{r} p=ggplot(tips, aes(tip,total_bill,)) + geom_point(aes(color=sex)) + facet_wrap("day",ncol = 3) p ``` # title,size,x y name,footnote ## add title ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex") p ``` ## add subtitle ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex",subtitle = "Subtitle of the plot") p ``` ## add footnote ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")+labs(caption = "this is footnote") p ``` ## adjust plot size ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")+theme( plot.margin = margin(2, 2, 5, 5, "cm")) p ``` ## adjust text size and center title ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ ggtitle("tip by sex")+labs(caption = "this is footnote") p+theme(plot.title = element_text(hjust = 0.5),text = element_text(size = 30)) ``` ## change x y name ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+xlab("new x name") + ylab("new y name") p ``` ## add chinese ```{r} library(showtext) showtext_auto() p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="新的 x name")+ scale_y_continuous(name="新的 y name") p ``` ## x y break and scales limit ### x scales limit ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p+ xlim(min=0, 20) ``` ### y scales limit ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p+ ylim(0, 100) ``` ### adding second aix ```{r} data002= data001%>% group_by(year,continent) %>% summarise(pop=sum(pop),lifeExp=mean(lifeExp))%>%filter(continent=='Asia') ``` remove scientific notation ```{r} coeff=1/40000000 p=ggplot(data002, aes(year, pop)) + geom_col() + geom_line(aes(year,lifeExp/ coeff),size=2, color = "red") +scale_y_continuous("pop", sec.axis = sec_axis(~.*coeff, name = "lifeExp"),labels = scales::comma) p ``` # applying themes ::: {.panel-tabset .nav-pills} ## theme_bw() ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p+ theme_bw() ``` ## theme_light() ```{r} p+ theme_light() ``` ## theme_economist() ```{r} library("ggthemes") p+ theme_economist() ``` ## theme_tufte() ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p+ theme_tufte() ``` ## theme_wsj() ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p+ theme_wsj() ``` ## theme_fivethirtyeight() ```{r} p=ggplot(tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p+ theme_fivethirtyeight() ``` ::: # convert ggplot to plotly ```{r} p=ggplot(data=tips, aes(tip, total_bill,color=sex)) + geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") pp=ggplotly(p) pp ``` # Save plot ```{r} p+ theme_economist() ggsave("myplot.png") ``` # add image into the chart ## add logo ```{r} # Add your company's logo to the graph you created logo <- image_read("logo.png") p grid::grid.raster(logo, x = 0.1, y = 0, just = c('left', 'bottom'), width = unit(0.4, 'inches')) ``` ## add background image ```{r} img4=image_read("bee.png") "bee.png" p=ggplot(tips, aes(tip, total_bill,color=sex)) + background_image(img4) +geom_point()+ scale_x_continuous(name="new x name")+ scale_y_continuous(name="new y name") p ``` # Animation plot ```{r} #pak::pak('thomasp85/gganimate') library(gganimate) p=ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) + geom_point(alpha = 0.7, show.legend = FALSE) + scale_colour_manual(values = country_colors) + scale_size(range = c(2, 12)) + scale_x_log10() + # Here comes the gganimate specific bits # labs(title = 'Year: {frame_time}', x = 'GDP per capita', y = 'life expectancy',colour = "country") + labs(title ='Year: {as.integer(frame_time)}', x = 'GDP per capita', y = 'life expectancy',colour = "country") + transition_time(year) + ease_aes('linear') p ``` # ggplot2 extension packages https://www.youtube.com/watch?v=efj6-aawubs&list=PLBnFxG6owe1FcJnrNbaIJyALHMyoKW27T ## patchwork The goal of patchwork is to make it ridiculously simple to combine separate ggplots into the same graphic. ```{r} #pak::pak('patchwork') ``` ```{r} library(ggplot2) library(patchwork) p1 <- ggplot(mtcars) + geom_point(aes(mpg, disp)) p2 <- ggplot(mtcars) + geom_boxplot(aes(gear, disp, group = gear)) p3 <- ggplot(mtcars) + geom_smooth(aes(disp, qsec)) p4 <- ggplot(mtcars) + geom_bar(aes(carb)) (p1 | p2 | p3) / p4 ``` ## legendry The goal of legendry is to provide additional guide functionality to the ggplot2 ecosystem. ```{r} #pak::pak('legendry') ``` ```{r} library(ggplot2) library(legendry) ``` ```{r} base <- ggplot(mpg, aes(displ, hwy, colour = cty)) + geom_point() + labs( x = "Engine displacement", y = "Highway miles per gallon", col = "City miles\nper gallon" ) + theme(axis.line = element_line()) ``` ```{r} # A partial guide to display a bracket efficient_bracket <- primitive_bracket( # Keys determine what is displayed key = key_range_manual(start = 25, end = Inf, name = "Efficient"), bracket = "square", # We want vertical text theme = theme( legend.text = element_text(angle = 90, hjust = 0.5), axis.text.y.left = element_text(angle = 90, hjust = 0.5) ) ) base + guides(y = guide_axis_stack("axis", efficient_bracket)) ``` ## marquee ## ggiraph ## geomtextpath ## ggpattern ## ggbump ## gghighlight ## ggdist # reference: https://cran.r-project.org/web/packages/magick/vignettes/intro.html https://yutannihilation.github.io/allYourFigureAreBelongToUs/ggthemes/