ggmatplot {ggmatplot} | R Documentation |
ggmatplot
Description
ggmatplot
is a quick and easy way of plotting the columns of two matrices
or data frames against each other using
ggplot2
.
Usage
ggmatplot(
x = NULL,
y = NULL,
plot_type = c("point", "line", "both", "density", "histogram", "boxplot", "dotplot",
"errorplot", "violin", "ecdf"),
color = NULL,
fill = NULL,
shape = NULL,
linetype = NULL,
xlim = c(NA, NA),
ylim = c(NA, NA),
log = NULL,
main = NULL,
xlab = NULL,
ylab = NULL,
legend_label = NULL,
legend_title = NULL,
desc_stat = "mean_se",
asp = NA,
...
)
Arguments
x , y |
Vectors or matrices of data.
|
plot_type |
A string specifying the type of plot. Possible plot types
are |
color , fill |
Vectors of colors. Defining only one of them will update
both
|
shape , linetype |
A vector of shapes or line types respectively.
|
xlim , ylim |
Ranges of x and y axes.
|
log |
A string defining which axes to transform into a log scale.
( |
main , xlab , ylab , legend_title |
Strings to update plot title, x axis label, y axis label and legend title respectively. |
legend_label |
A vector of strings, to rename the legend labels. |
desc_stat |
Descriptive statistics to be used for visualizing errors,
in |
asp |
The y/x aspect ratio. |
... |
Other arguments passed on to the plot. Possible arguments are those that can be passed on to the underlying ggplot layers. |
Value
A ggplot object. The columns of the input matrices will be plotted against each other using the defined plot type.
Plot Types
ggmatplot
plots are built upon ggplot2 layers
. The following is a list of
ggmatplot
plot types, along with their underlying
ggplot geoms
or stats
.
-
point
geom_point
-
line
geom_line
-
both
geom_point
+geom_line
-
density
geom_density
-
histogram
geom_histogram
-
boxplot
geom_boxplot
-
dotplot
geom_dotplot
-
errorplot
geom_pointrange
-
violin
geom_violin
-
ecdf
stat_ecdf
Examples
# Define a data set
iris_sub <- subset(iris, Species == "setosa")
ggmatplot(iris_sub[, c(1, 3)], iris_sub[, c(2, 4)])
# Modify legend label and axis
ggmatplot(iris_sub[, c(1, 3)], iris_sub[, c(2, 4)],
shape = c(4, 6),
legend_label = c("Sepal", "Petal"), legend_title = "",
xlab = "Length", ylab = "Width"
)