# Mindanao State University
# General Santos City
# Submitted by: Roland Fritz C. Adam & AJ Ardaniel
# ggplot2 Tutorial 2 - Theme
# Setup
options(scipen=999)
library(ggplot2)
data("midwest", package = "ggplot2")
theme_set(theme_bw())
# midwest <- read.csv("http://goo.gl/G1K41K") # bkup data source
# Add plot components --------------------------------
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
# Call plot ------------------------------------------
plot(gg)
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 15 rows containing missing values (`geom_point()`).
# Adding Plot and Axis Titles
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
# Modify theme components -------------------------------------------
gg + theme(plot.title=element_text(size=20,
face="bold",
family="American Typewriter",
color="tomato",
hjust=0.5,
lineheight=1.2), # title
plot.subtitle=element_text(size=15,
family="American Typewriter",
face="bold",
hjust=0.5), # subtitle
plot.caption=element_text(size=15), # caption
axis.title.x=element_text(vjust=10,
size=15), # X axis title
axis.title.y=element_text(size=15), # Y axis title
axis.text.x=element_text(size=10,
angle = 30,
vjust=.5), # X axis text
axis.text.y=element_text(size=10)) # Y axis text
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# Modifying Legend
# Method 1: Using labs()
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
gg + labs(color="State", size="Density") # modify legend title
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# Method 2: Using guides()
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
gg <- gg + guides(color=guide_legend("State"), size=guide_legend("Density")) # modify legend title
plot(gg)
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# Method 3: Using scale_aesthetic_vartype() format
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
# Modify Legend
gg + scale_color_discrete(name="State") + scale_size_continuous(name = "Density", guide = FALSE) # turn off legend for size
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
## Warning: The `guide` argument in `scale_*()` cannot be `FALSE`. This was deprecated in
## ggplot2 3.3.4.
## ℹ Please use "none" instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
# How to Change Legend Labels and Point Colors for Categories
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
gg + scale_color_manual(name="State",
labels = c("Illinois",
"Indiana",
"Michigan",
"Ohio",
"Wisconsin"),
values = c("IL"="blue",
"IN"="red",
"MI"="green",
"OH"="brown",
"WI"="orange"))
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 15 rows containing missing values (`geom_point()`).
# Change the Order of Legend
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
gg + guides(colour = guide_legend(order = 1),
size = guide_legend(order = 2))
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# How to Style the Legend Title, Text and Key
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
gg + theme(legend.title = element_text(size=12, color = "firebrick"),
legend.text = element_text(size=10),
legend.key=element_rect(fill='springgreen')) +
guides(colour = guide_legend(override.aes = list(size=2, stroke=1.5)))
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# How to Remove the Legend and Change Legend Positions
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
# No legend --------------------------------------------------
gg + theme(legend.position="None") + labs(subtitle="No Legend")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# Legend to the left -----------------------------------------
gg + theme(legend.position="left") + labs(subtitle="Legend on the Left")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# legend at the bottom and horizontal ------------------------
gg + theme(legend.position="bottom", legend.box = "horizontal") + labs(subtitle="Legend at Bottom")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# legend at bottom-right, inside the plot --------------------
gg + theme(legend.title = element_text(size=12, color = "salmon", face="bold"),
legend.justification=c(1,0),
legend.position=c(0.95, 0.05),
legend.background = element_blank(),
legend.key = element_blank()) +
labs(subtitle="Legend: Bottom-Right Inside the Plot")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# legend at top-left, inside the plot -------------------------
gg + theme(legend.title = element_text(size=12, color = "salmon", face="bold"),
legend.justification=c(0,1),
legend.position=c(0.05, 0.95),
legend.background = element_blank(),
legend.key = element_blank()) +
labs(subtitle="Legend: Top-Left Inside the Plot")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# 3. Adding Text, Label and Annotation
# How to Add Text and Label around the Points
library(ggplot2)
# Filter required rows.
midwest_sub <- midwest[midwest$poptotal > 300000, ]
midwest_sub$large_county <- ifelse(midwest_sub$poptotal > 300000, midwest_sub$county, "")
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
# Plot text and label ------------------------------------------------------
gg + geom_text(aes(label=large_county), size=2, data=midwest_sub) + labs(subtitle="With ggplot2::geom_text") + theme(legend.position = "None") # text
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
## Warning: Removed 14 rows containing missing values (`geom_text()`).
gg + geom_label(aes(label=large_county), size=2, data=midwest_sub, alpha=0.25) + labs(subtitle="With ggplot2::geom_label") + theme(legend.position = "None") # label
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 15 rows containing missing values (`geom_point()`).
## Warning: Removed 14 rows containing missing values (`geom_label()`).
# Plot text and label that REPELS eachother (using ggrepel pkg) ------------
install.packages('ggrepel')
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)
library(ggrepel)
gg + geom_text_repel(aes(label=large_county), size=2, data=midwest_sub) + labs(subtitle="With ggrepel::geom_text_repel") + theme(legend.position = "None") # text
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 15 rows containing missing values (`geom_point()`).
## Warning: Removed 14 rows containing missing values (`geom_text_repel()`).
gg + geom_label_repel(aes(label=large_county), size=2, data=midwest_sub) + labs(subtitle="With ggrepel::geom_label_repel") + theme(legend.position = "None") # label
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 15 rows containing missing values (`geom_point()`).
## Warning: Removed 14 rows containing missing values (`geom_label_repel()`).
# How to Add Annotations Anywhere inside Plot
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest")
# Define and add annotation -------------------------------------
library(grid)
my_text <- "This text is at x=0.7 and y=0.8!"
my_grob = grid.text(my_text, x=0.7, y=0.8, gp=gpar(col="firebrick", fontsize=14, fontface="bold"))
gg + annotation_custom(my_grob)
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Warning: Removed 15 rows containing missing values (`geom_point()`).
# 4. Flipping and Reversing X and Y Axis
# How to flip the X and Y axis?
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest", subtitle="X and Y axis Flipped") + theme(legend.position = "None")
# Flip the X and Y axis -------------------------------------------------
gg + coord_flip()
## `geom_smooth()` using formula = 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (`stat_smooth()`).
## Removed 15 rows containing missing values (`geom_point()`).
# How to reverse the scale of an axis?
library(ggplot2)
# Base Plot
gg <- ggplot(midwest, aes(x=area, y=poptotal)) +
geom_point(aes(col=state, size=popdensity)) +
geom_smooth(method="loess", se=F) + xlim(c(0, 0.1)) + ylim(c(0, 500000)) +
labs(title="Area Vs Population", y="Population", x="Area", caption="Source: midwest", subtitle="Axis Scales Reversed") + theme(legend.position = "None")
# Reverse the X and Y Axis ---------------------------
gg + scale_x_reverse() + scale_y_reverse()
## Scale for x is already present.
## Adding another scale for x, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## `geom_smooth()` using formula = 'y ~ x'
# 5. Faceting: Draw multiple plots within one figure
library(ggplot2)
data(mpg, package="ggplot2") # load data
# mpg <- read.csv("http://goo.gl/uEeRGu") # alt data source
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
labs(title="hwy vs displ", caption = "Source: mpg") +
geom_smooth(method="lm", se=FALSE) +
theme_bw() # apply bw theme
plot(g)
## `geom_smooth()` using formula = 'y ~ x'
# Facet Wrap
library(ggplot2)
# Base Plot
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
geom_smooth(method="lm", se=FALSE) +
theme_bw() # apply bw theme
# Facet wrap with common scales
g + facet_wrap( ~ class, nrow=3) + labs(title="hwy vs displ", caption = "Source: mpg", subtitle="Ggplot2 - Faceting - Multiple plots in one figure") # Shared scales
## `geom_smooth()` using formula = 'y ~ x'
# Facet wrap with free scales
g + facet_wrap( ~ class, scales = "free") + labs(title="hwy vs displ", caption = "Source: mpg", subtitle="Ggplot2 - Faceting - Multiple plots in one figure with free scales") # Scales free
## `geom_smooth()` using formula = 'y ~ x'
# Facet Grid
library(ggplot2)
# Base Plot
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
labs(title="hwy vs displ", caption = "Source: mpg", subtitle="Ggplot2 - Faceting - Multiple plots in one figure") +
geom_smooth(method="lm", se=FALSE) +
theme_bw() # apply bw theme
# Add Facet Grid
g1 <- g + facet_grid(manufacturer ~ class) # manufacturer in rows and class in columns
plot(g1)
## `geom_smooth()` using formula = 'y ~ x'
library(ggplot2)
# Base Plot
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
geom_smooth(method="lm", se=FALSE) +
labs(title="hwy vs displ", caption = "Source: mpg", subtitle="Ggplot2 - Facet Grid - Multiple plots in one figure") +
theme_bw() # apply bw theme
# Add Facet Grid
g2 <- g + facet_grid(cyl ~ class) # cyl in rows and class in columns.
plot(g2)
## `geom_smooth()` using formula = 'y ~ x'
install.packages('gridExtra')
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)
# Draw Multiple plots in same figure.
library(gridExtra)
gridExtra::grid.arrange(g1, g2, ncol=2)
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
# 6. Modifying Plot Background, Major and Minor Axis
# How to Change Plot background
library(ggplot2)
# Base Plot
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
geom_smooth(method="lm", se=FALSE) +
theme_bw() # apply bw theme
# Change Plot Background elements -----------------------------------
g + theme(panel.background = element_rect(fill = 'khaki'),
panel.grid.major = element_line(colour = "burlywood", size=1.5),
panel.grid.minor = element_line(colour = "tomato",
size=.25,
linetype = "dashed"),
panel.border = element_blank(),
axis.line.x = element_line(colour = "darkorange",
size=1.5,
lineend = "butt"),
axis.line.y = element_line(colour = "darkorange",
size=1.5)) +
labs(title="Modified Background",
subtitle="How to Change Major and Minor grid, Axis Lines, No Border")
## Warning: The `size` argument of `element_line()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## `geom_smooth()` using formula = 'y ~ x'
# Change Plot Margins -----------------------------------------------
g + theme(plot.background=element_rect(fill="salmon"),
plot.margin = unit(c(2, 2, 1, 1), "cm")) + # top, right, bottom, left
labs(title="Modified Background", subtitle="How to Change Plot Margin")
## `geom_smooth()` using formula = 'y ~ x'
# How to Remove Major and Minor Grid, Change Border, Axis Title, Text and Ticks
library(ggplot2)
# Base Plot
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
geom_smooth(method="lm", se=FALSE) +
theme_bw() # apply bw theme
g + theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
axis.title = element_blank(),
axis.text = element_blank(),
axis.ticks = element_blank()) +
labs(title="Modified Background", subtitle="How to remove major and minor axis grid, border, axis title, text and ticks")
## `geom_smooth()` using formula = 'y ~ x'
# Add an Image in Background
install.packages('png')
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)
install.packages('grid')
## Installing package into '/cloud/lib/x86_64-pc-linux-gnu-library/4.3'
## (as 'lib' is unspecified)
## Warning: package 'grid' is a base package, and should not be updated
library(ggplot2)
library(grid)
library(png)
img <- png::readPNG("Rlogo.png") # source: https://www.r-project.org/
g_pic <- rasterGrob(img,interpolate=TRUE)
# Base Plot
g <- ggplot(mpg, aes(x=displ, y=hwy)) +
geom_point() +
geom_smooth(method="lm", se=FALSE) +
theme_bw() # apply bw theme
g + theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
plot.title = element_text(size = rel(1.5), face = "bold"),
axis.ticks = element_blank()) +
annotation_custom(g_pic, xmin=5, xmax=7, ymin=30, ymax=45)
## `geom_smooth()` using formula = 'y ~ x'
