Ggplot2: Difference between revisions

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= text annotations: [https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html ggrepel] package =
= text annotations: [https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html ggrepel] package =
* [https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html ggrepel] package. Found on [https://simplystatistics.org/2018/01/22/the-dslabs-package-provides-datasets-for-teaching-data-science/ Some datasets for teaching data science] by Rafael Irizarry.
* [https://cran.r-project.org/web/packages/ggrepel/vignettes/ggrepel.html ggrepel] package. Found on [https://simplystatistics.org/2018/01/22/the-dslabs-package-provides-datasets-for-teaching-data-science/ Some datasets for teaching data science] by Rafael Irizarry.
* [https://r4ds.had.co.nz/graphics-for-communication.html#annotations Annotations] from the chapter ''Graphics for communication'' of ''R for Data Science'' by Grolemund & Hadley
* [http://www.sthda.com/english/wiki/ggplot2-texts-add-text-annotations-to-a-graph-in-r-software ggplot2 texts : Add text annotations to a graph in R software]. The functions [https://ggplot2.tidyverse.org/reference/geom_text.html geom_text()] and [https://ggplot2.tidyverse.org/reference/annotate.html annotate()] can be used to add a text annotation at a particular coordinate/position.
* [http://www.sthda.com/english/wiki/ggplot2-texts-add-text-annotations-to-a-graph-in-r-software ggplot2 texts : Add text annotations to a graph in R software]. The functions [https://ggplot2.tidyverse.org/reference/geom_text.html geom_text()] and [https://ggplot2.tidyverse.org/reference/annotate.html annotate()] can be used to add a text annotation at a particular coordinate/position.
* https://ggplot2-book.org/annotations.html
* https://ggplot2-book.org/annotations.html

Revision as of 08:37, 19 November 2019

ggplot2

Books

Tutorials

Extensions

http://www.ggplot2-exts.org/gallery/

Some examples

Examples from 'R for Data Science' book - Aesthetic mappings

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy))
  # the 'mapping' is the 1st argument for all geom_* functions, so we can safely skip it.
# template
ggplot(data = <DATA>) + 
  <GEOM_FUNCTION>(mapping = aes(<MAPPINGS>))

# add another variable through color, size, alpha or shape
ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy, color = class))

ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy, size = class))

ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy, alpha = class))

ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy, shape = class))

ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy), color = "blue")

# add another variable through facets
ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy)) + 
  facet_wrap(~ class, nrow = 2)

# add another 2 variables through facets
ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy)) + 
  facet_grid(drv ~ cyl)

Examples from 'R for Data Science' book - Geometric objects

# Points
ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy))

# Smoothed
ggplot(data = mpg) + 
  geom_smooth(aes(x = displ, y = hwy))

# Points + smoother
ggplot(data = mpg) + 
  geom_point(aes(x = displ, y = hwy)) +
  geom_smooth(aes(x = displ, y = hwy))

# Colored points + smoother
ggplot(data = mpg, aes(x = displ, y = hwy)) + 
  geom_point(aes(color = class)) + 
  geom_smooth()

Examples from 'R for Data Science' book - Transformation

# y axis = counts
# bar plot
ggplot(data = diamonds) + 
  geom_bar(aes(x = cut))
# Or
ggplot(data = diamonds) + 
  stat_count(aes(x = cut))

# y axis = proportion
ggplot(data = diamonds) + 
  geom_bar(aes(x = cut, y = ..prop.., group = 1))

# bar plot with 2 variables
ggplot(data = diamonds) + 
  geom_bar(aes(x = cut, fill = clarity))

facet_wrap and facet_grid to create a panel of plots

Color palette

Color picker

https://github.com/daattali/colourpicker

scales packages - ggplot2 default color palette

Emulate ggplot2 default color palette

Answer 1 

gg_color_hue <- function(n) {
  hues = seq(15, 375, length = n + 1)
  hcl(h = hues, l = 65, c = 100)[1:n]
}

n = 4
cols = gg_color_hue(n)

dev.new(width = 4, height = 4)
plot(1:n, pch = 16, cex = 2, col = cols)

Answer 2 (better, it shows the color values in HEX). It should be read from left to right and then top to down.

scales package 

library(scales)
show_col(hue_pal()(4))
show_col(hue_pal()(2)) # (salmon, iris blue) 
           # see https://www.htmlcsscolor.com/ for color names

Class variables

"Set1" is a good choice. See RColorBrewer::display.brewer.all()

Heatmap for single channel

https://scales.r-lib.org/ 

# White <----> Blue
RColorBrewer::display.brewer.pal(n = 8, name = "Blues")

Heatmap for dual channels

http://www.sthda.com/english/wiki/colors-in-r 

library(RcolorBrewer)
# Red <----> Blue
display.brewer.pal(n = 8, name = 'RdBu')
# Hexadecimal color specification 
brewer.pal(n = 8, name = "RdBu")

plot(1:8, col=brewer_pal(palette = "RdBu")(8), pch=20, cex=4)

# Blue <----> Red
plot(1:8, col=rev(brewer_pal(palette = "RdBu")(8)), pch=20, cex=4)

Twopalette.svg

Themes and background for ggplot2

ggthmr

ggthmr package

ggsci

https://nanx.me/ggsci/

Common plots

https://ggplot2.tidyverse.org/reference/index.html

Line plots

Histogram

ggplot(data = txhousing, aes(x = median)) +
  geom_histogram()

Boxplot with jittering

ggplot(data.frame(Wi), aes(y = Wi)) + 
  geom_boxplot()
# df2 is n x 2 
ggplot(df2, aes(x=nboot, y=boot)) +
  geom_boxplot(outlier.shape=NA) + #avoid plotting outliers twice
  geom_jitter(aes(color=nboot), position=position_jitter(width=.2, height=0)) +
  labs(title="", y = "", x = "nboot")

If we omit the outlier.shape=NA option in geom_boxplot(), we will get the following plot.

Jitterboxplot.png

Violin plot

library(ggplot2)
ggplot(midwest, aes(state, area)) + geom_violin() + ggforce::geom_sina()

Violinplot.png

Kernel density plot

Back to back barplot

Bivariate analysis with ggpair

Correlation in R: Pearson & Spearman with Matrix Example

Ordered barplot and facet

Reordering and facetting for ggplot2

Aesthetics

group

https://ggplot2.tidyverse.org/reference/aes_group_order.html

GUI

ggedit & ggplotgui – interactive ggplot aesthetic and theme editor

esquisse (French, means 'sketch'): creating ggplot2 interactively

https://cran.rstudio.com/web/packages/esquisse/index.html

A 'shiny' gadget to create 'ggplot2' charts interactively with drag-and-drop to map your variables. You can quickly visualize your data accordingly to their type, export to 'PNG' or 'PowerPoint', and retrieve the code to reproduce the chart.

The interface introduces basic terms used in ggplot2:

  • x, y,
  • fill (useful for bars & boxplot & 2D density, not useful for scatterplot),
  • color,
  • size,
  • facet, split up your data by one or more variables and plot the subsets of data together.

It does not include all features in ggplot2. At the bottom of the interface,

  • Labels & title & caption.
  • Plot options. Palette, theme, legend position.
  • Data. Remove subset of data.
  • Export & code. Copy/save the R code. Export file as PNG or PowerPoint.

plotly

R → plotly

ggconf: Simpler Appearance Modification of 'ggplot2'

https://github.com/caprice-j/ggconf

Plotting individual observations and group means

https://drsimonj.svbtle.com/plotting-individual-observations-and-group-means-with-ggplot2

subplot

Easy way to mix multiple graphs on the same page

gridExtra

Force a regular plot object into a Grob for use in grid.arrange

gridGraphics package

make one panel blank/create a placeholder

https://stackoverflow.com/questions/20552226/make-one-panel-blank-in-ggplot2

labs

x and y labels

https://stackoverflow.com/questions/10438752/adding-x-and-y-axis-labels-in-ggplot2 or the Labels part of the cheatsheet

You can set the labels with xlab() and ylab(), or make it part of the scale_*.* call. 

labs(x = "sample size", y = "ngenes (glmnet)")

name-value pairs

See several examples (color, fill, size, ...) from opioid prescribing habits in texas.

Prevent sorting of x labels

See Change the order of a discrete x scale.

The idea is to set the levels of x variable. 

junk   # n x 2 table
colnames(junk) <- c("gset", "boot")
junk$gset <- factor(junk$gset, levels = as.character(junk$gset))
ggplot(data = junk, aes(x = gset, y = boot, group = 1)) + 
  geom_line() + 
  theme(axis.text.x=element_text(color = "black", angle=30, vjust=.8, hjust=0.8))

Legend title

scale_colour_manual("Treatment", values = c("black", "red"))

Hide legend

gg + theme(legend.position="none")

See Remove legend ggplot 2.2, How to remove legend from a ggplot.

ylim and xlim in ggplot2

https://stackoverflow.com/questions/3606697/how-to-set-limits-for-axes-in-ggplot2-r-plots or the Zooming part of the cheatsheet

Use one of the following

  • + scale_x_continuous(limits = c(-5000, 5000))
  • + coord_cartesian(xlim = c(-5000, 5000))
  • + xlim(-5000, 5000)

Center title

See the Legends part of the cheatsheet. 

ggtitle("MY TITLE") +
  theme(plot.title = element_text(hjust = 0.5))

margins

https://stackoverflow.com/a/10840417

Time series plot

Multiple lines plot https://stackoverflow.com/questions/14860078/plot-multiple-lines-data-series-each-with-unique-color-in-r 

set.seed(45)
nc <- 9
df <- data.frame(x=rep(1:5, nc), val=sample(1:100, 5*nc), 
                   variable=rep(paste0("category", 1:nc), each=5))
# plot
# http://colorbrewer2.org/#type=qualitative&scheme=Paired&n=9
ggplot(data = df, aes(x=x, y=val)) + 
    geom_line(aes(colour=variable)) + 
    scale_colour_manual(values=c("#a6cee3", "#1f78b4", "#b2df8a", "#33a02c", "#fb9a99", "#e31a1c", "#fdbf6f", "#ff7f00", "#cab2d6"))

Versus old fashion 

dat <- matrix(runif(40,1,20),ncol=4) # make data
matplot(dat, type = c("b"),pch=1,col = 1:4) #plot
legend("topleft", legend = 1:4, col=1:4, pch=1) # optional legend

Github style calendar plot

geom_errorbar(): error bars

set.seed(301)
x <- rnorm(10)
SE <- rnorm(10)
y <- 1:10

par(mfrow=c(2,1))
par(mar=c(0,4,4,4))
xlim <- c(-4, 4)
plot(x[1:5], 1:5, xlim=xlim, ylim=c(0+.1,6-.1), yaxs="i", xaxt = "n", ylab = "", pch = 16, las=1)
mtext("group 1", 4, las = 1, adj = 0, line = 1) # las=text rotation, adj=alignment, line=spacing
par(mar=c(5,4,0,4))
plot(x[6:10], 6:10, xlim=xlim, ylim=c(5+.1,11-.1), yaxs="i", ylab ="", pch = 16, las=1, xlab="")
arrows(x[6:10]-SE[6:10], 6:10, x[6:10]+SE[6:10], 6:10, code=3, angle=90, length=0)
mtext("group 2", 4, las = 1, adj = 0, line = 1)

Stklnpt.svg

text annotations: ggrepel package

Fonts

Adding Custom Fonts to ggplot in R

Save the plots

ggsave() We can specify dpi to increase the resolution. For example, 

g1 <- ggplot(data = mydf) 
g1
ggsave("myfile.png", g1, height = 7, width = 8, units = "in", dpi = 500)

graphics::smoothScatter

smoothScatter with ggplot2

BBC

Add your brand to ggplot graph

You Need to Start Branding Your Graphs. Here's How, with ggplot!

Python

plotnine: A Grammar of Graphics for Python.

plotnine is an implementation of a grammar of graphics in Python, it is based on ggplot2. The grammar allows users to compose plots by explicitly mapping data to the visual objects that make up the plot.

The Hitchhiker’s Guide to Plotnine

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