Plotting Vertically
The vertical orientation combines the plots and these plots are placed side by side with each other. We will take the above ggplot2 plots and add them to arrange them vertically. The + operator is used to arrange these plots side by side in the same graph.
Example: Vertically arrange plots in the same frame
R
library(ggplot2) library(patchwork) data(iris) head(iris) gfg1 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_bar(stat = "identity") gfg2 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_point() gfg3 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_line() # Combination of plots by arranging them side by side gfg_comb_1 <- gfg1 + gfg2 + gfg3 gfg_comb_1 |
Output :
Vertical orientation
Draw Composition of Plots Using the patchwork Package in R
In this article, we will discuss how to draw a composition of plots using the patchwork package in R programming language. The patchwork package makes it easier to plot different ggplots in a single graph. We will require both ggplot2 packages for plotting our data and the patchwork package to combine the different ggplots.
Let us first draw all the plots normally and independently.
Example: Plotting the dataset in a bar plot
R
library(ggplot2) library(patchwork) data(iris) head(iris) # Plotting the bar chart gfg1 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_bar(stat = "identity") gfg1 |
Output :
Bar plot
Example: Plotting the dataset in a scatterplot
R
library(ggplot2) library(patchwork) data(iris) head(iris) # Scatterplot gfg2 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_point() gfg2 |
Output :
Scatterplot
Example: Plotting the dataset in a line plot
R
library(ggplot2) library(patchwork) data(iris) head(iris) # Line plot gfg3 <- ggplot(iris, aes(Sepal.Length, Petal.Length, color = Species)) + geom_line() gfg3 |
Output :
Line plot
Now let us look at how these three plots can be combined in various orientations.
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