# Graphics in R (Gallery with Examples)

This page shows an overview of (almost all) different types of graphics, plots, charts, diagrams, and figures of the R programming language.

Here is a list of all graph types that are illustrated in this article:

Each type of graphic is illustrated with some basic example code. These codes are based on the following data:

```set.seed(123) # Set seed for reproducibility x <- rnorm(30) # Create x variable y <- x + rnorm(30) # Create correlated y variable```

In each section, you can find additional resources on how to create and modify these graphic types yourself (including reproducible R syntax and many examples).

So without further ado, let’s dive in!

## Barplot

Barplot Definition: A barplot (or barchart; bargraph) illustrates the association between a numeric and a categorical variable. The barplot represents each category as a bar and reflects the corresponding numeric value with the bar’s size.

The following R syntax shows how to draw a basic barplot in R:

`barplot(x) # Draw barplot in R`

Our example barplot looks a follows: Advanced Barplots: Find some advanced barplots below. Click on the images to get more information and example R codes for each of the barplots.

Barplot Resources: Find some further resources on the creation of barplots below.

Barplot Video Tutorial: The following video shows a tutorial on creating barplots in R.

## Boxplot

Boxplot Definition: A boxplot (or box-and-whisker plot) displays the distribution of a numerical variable based on five summary statistics: minimum non-outlier; first quartile; median; third quartile; and maximum non-outlier. Furthermore, boxplots show the positioning of outliers and whether the data is skewed.

The following R syntax shows how to draw a basic boxplot in R:

`boxplot(x) # Draw boxplot in R` Advanced Boxplots: Find some advanced boxplots below. Click on the images to get more information and example R codes for each of the boxplots.

Boxplot Resources: Find some further resources on the creation of boxplots below.

Boxplot Video Tutorial: The following video shows a tutorial on creating boxplots in R.

## Density Plot

Density Plot Definition: A density plot (or kernel density plot; density trace graph) shows the distribution of a numerical variable over a continuous interval. Peaks of a density plot visualize where the values of numerical variables are concentrated.

The following R syntax shows how to draw a basic density plot in R:

`plot(density(x)) # Draw density plot in R` Advanced Density Plots: Find some advanced density plots below. Click on the images to get more information and example R codes for each of the density plots.

Density Plot Resources: Find some further resources on the creation of density plots below.

## Heatmap

Heatmap Definition: A heatmap (or shading matrix) visualizes individual values of a matrix with colors. More common values are typically indicated by brighter reddish colors and less common values are typically indicated by darker colors.

The following R syntax shows how to draw a basic heatmap in R:

`heatmap(cbind(x, y)) # Draw heatmap in R` Advanced Heatmaps: Find some advanced heatmaps below. Click on the images to get more information and example R codes for each of the heatmaps .

Heatmap Resources: Find some further resources on the creation of heatmaps below.

Heatmap Video Tutorial: The following video shows a tutorial on creating heatmaps in R.

## Line Plot

Line Plot Definition: A line plot (or line graph; line chart) visualizes values along a sequence (e.g. over time). Line plots consist of an x-axis and a y-axis. The x-axis usually displays the sequence and the y-axis the values corresponding to each point of the sequence.

The following R syntax shows how to draw a basic line plot in R:

`plot(1:length(y), y, type = "l") # Draw line plot in R` Advanced Line Plots: Find some advanced line plots below. Click on the images to get more information and example R codes for each of the line plots.

Line Plot Resources: Find some further resources on the creation of line plots below.

## Histogram

Histogram Definition: A histogram groups continuous data into ranges and plots this data as bars. The height of each bar shows the amount of observations within each range.

The following R syntax shows how to draw a basic histogram in R:

`hist(x) # Draw histogram in R` Advanced Histograms: Find some advanced histograms below. Click on the images to get more information and example R codes for each of the histograms.

Histogram Resources: Find some further resources on the creation of histograms below.

Histogram Video Tutorial: The following video shows a tutorial on creating histograms in R.

## Pairs Plot

Pairs Plot Definition: A pairs plot is a plot matrix, consisting of scatterplots for each variable-combination of a data frame.

The following R syntax shows how to draw a basic pairs plot in R:

`pairs(data.frame(x, y)) # Draw pairs plot in R` Advanced Pairs Plots: Find some advanced pairs plots below. Click on the images to get more information and example R codes for each of the pairs plots.

Pairs Plot Resources: Find some further resources on the creation of pairs plots below.

## Polygon Plot

Polygon Plot Definition: A polygon plot displays a plane geometric figure (i.e. a polygon) within the plot.

The following R syntax shows how to draw a basic polygon plot in R:

```plot(1, 1, # Draw polygon plot in R col = "white", xlab = "X", ylab = "Y") polygon(x = c(0.7, 1.3, 1.3, 0.8), y = c(0.6, 1.0, 1.4, 1.3), col = "#353436")``` Advanced Polygon Plots: Find some advanced polygon plots below. Click on the images to get more information and example R codes for each of the polygon plots.

Polygon Plot Resources: Find some further resources on the creation of polygon plots below.

## QQplot

QQplot Definition: A QQplot (or Quantile-Quantile plot; Quantile-Quantile diagram) determines whether two data sources come from a common distribution. QQplots draw the quantiles of the two numerical data sources against each other. If both data sources come from the same distribution, the points fall on a 45 degree angle.

The following R syntax shows how to draw a basic QQplot in R:

`qqplot(x, y) # Draw QQplot in R` Advanced QQplots: Find some advanced QQplots below. Click on the images to get more information and example R codes for each of the QQplots.

QQplot Resources: Find some further resources on the creation of QQplots below.

## Scatterplot

Scatterplot Definition: A scatterplot (or scatter plot; scatter graph; scatter chart; scattergram; scatter diagram) displays two numerical variables with points, whereby each point represents the value of one variable on the x-axis and the value of the other variable on the y-axis.

The following R syntax shows how to draw a basic scatterplot in R:

`plot(x, y) # Draw scatterplot in R` Advanced Scatterplots: Find some advanced scatterplots below. Click on the images to get more information and example R codes for each of the scatterplots.

Scatterplot Resources: Find some further resources on the creation of scatterplots below.

## Venn Diagram

Venn Diagram Definition: A venn diagram (or primary diagram; set diagram; logic diagram) illustrates all possible logical relations between certain data characteristics. Each characteristic is represented as a circle, whereby overlapping parts of the circles illustrate elements that have both characteristics at the same time.

The following R syntax shows how to draw a basic venn diagram in R:

```install.packages("VennDiagram") # Install VennDiagram package library("VennDiagram") # Load VennDiagram package plot.new() # Draw empty plot draw.single.venn(area = 10) # Draw venn diagram``` Advanced Venn Diagrams: Find some advanced venn diagrams below. Click on the images to get more information and example R codes for each of the venn diagrams.

Venn Diagram Resources: Find some further resources on the creation of venn diagrams below.

Venn Diagram Video Tutorial: The following video shows a tutorial on creating venn diagrams in R.

## General Modification of Plots

In the previous part of this article, I have shown you many different types of plots. However, there are plenty of programming tricks for the modification of plots in general. In the following, you will find a list of tutorials that explain such general modifications of plots in R.

### ggplot2

This tutorial showed an overview of many different graphics and plots of the R programming language. If you want to learn more details about the creation of plots in R, I can recommend the following YouTube video of the DataCamp YouTube channel:

If you want to learn more about the R programming language in general, you could have a look at the following two links. They show a list of useful R functions…

… and give an overview of all R programming tutorials on this website:

I hope you liked this gallery of R graphics! If you have further questions or any kind of feedback, don’t hesitate to let me know in the comments below.