Graphical Representations in R

Many graphical representations in R Language are available for both qualitative and quantitative data types. In this post, we will only discuss graphical representations in R such as histograms, bar plots, and box plots.

Creating Histogram in R

To visualize a single variable, the histogram can be drawn using the hist() function in R. The use of histograms is to judge the shape and distribution of data in a graphical way. Histograms are also used to check the normality of the variable.

Let us attach the data from iris dataset.


We can enhance the histogram by using some arguments/parameters related to the hist() function in R. For example,

  xlab = "Petal Width",
  ylab = "Frequency",
  main = "Histogram of Petal Width from Iris Data set",
  breaks = 10,
  col = "dodgerblue",
  border = "orange")
Graphical Representations in R Language

If these arguments are not provided, R will attempt to intelligently guess them, especially the number of breaks. See the YouTube tutorial for graphical representations of the histogram.

Creating Barplots in R

The bar plots are the best choice for visual inspection of a categorical variable (or a numeric variable with a finite number of values), or a rank variable. Usually, one can use bar plots for comparison purposes. The barplot() function can be used for visual inspection of a categorical variable.

barplot( table(cyl) )
  ylab = "Frequency",
  xlab = "Cylinders (4, 6, 8)",
  main = "Number of cylinders ",
  col = "green",
  border = "blue")

Creating Boxplots in R

One can use Boxplots to visualize the normality, skewness, and existence of outliers in the data based on five-number summary statistics.


However, one can compare a numerical variable for different values of a categorical/grouping variable. For example,

boxplot(mpg ~ cyl, data = mtcars)
Graphical Representations in R Boxplot

The reads the formula mpg ~ cyl as: “Plot the mpg variable against the cyl variable using the dataset mtcars. The symbol ~ used to specify a formula in R.

boxplot(mpg ~ cyl, data =mtcars,
  xlab = "Cylinders",
  ylab = "Miles per Gallon",
  pch = 20,
  cex = 2,
  col = "pink",
  border = "black")

See How to perform descriptive statistics

Visit: MCQs and Quiz site

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