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Introduction to Data Analysis and Visualization with R

Density Plots

Explore how to create and customize density plots in R using both base plot functions and ggplot2. Understand how to visualize the probability distribution of continuous variables, adjust plot aesthetics like line thickness, color, and smoothing, and interpret data skewness and trends for better data exploration.

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Features

We use density plots to visualize the distribution of a continuous variable. The plot displays the density or probability of occurrence of data points along the x-axis, with the y-axis representing the probability density. This plot provides a smooth estimate of the data distribution, which helps us identify patterns and trends in the data. It is a valuable tool for exploring data and comparing the distributions of different variables or datasets.

Density chart
Density chart

Density plot with plot()

We use two different built-in functions to create a density plot in R. We first process the data in the density() function, and we supply it to the plot() function. The syntax structure is as follows:

# Syntax structure
plot(density(<data>))

Now, we will create a basic density plot using the mtcars dataset.

R
# We use `airquality` dataset in this exercise
head(mtcars)   # Preview of the dataset
plot(density(mtcars$mpg))  # Process the data and then plot the chart
  • Line 3: We first process the mpg column of the mtcars dataset and then supply it to
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