# Density And Histogram In R

This article will discuss using the density histogram in the R programming language together. First, we will go to find out what is the histogram and density together.

## What is the histogram in R?

A histogram is a visual that groups several data points into user-specified ranges and provides a rough idea of the distribution of numerical data. See the syntax for this function below.

Syntax:

hist(x, main, xlab, xlim, ylim, breaks, col, border)

Parameters:

• x: It is a vector including numeric values.
• main: The title of the chart.
• col: Set the color of the bars.
• border: Set the border color of each bar.
• xlab:  Describe the x-axis.
• xlim: The range of values on the x-axis.
• ylim: The range of values on the y-axis.
• breaks: The width of each bar.

## What is the density in R?

A density plot depicts a numeric variable’s distribution using a kernel density estimate to depict the variable’s probability density function. R Language’s density() function is used to generate kernel density estimates. Furthermore, its return value is utilized to construct the final density map. Follow the syntax below:

Syntax:

density(x)

Parameters:

• x: The data that needs to be computed.

## How to use the density and histogram in R?

### Using the hist() function in R to plot

First, we will create a vector for this example as follows:

# Create the vector
vec <- c(5, 3, 6, 9, 12, 6, 3, 2, 9, 10, 36)

# View the vector
vec

Output

[1]  5  3  6  9 12  6  3  2  9 10 36

Now, we will use the hist() function in R to plot the chart with this vector.

# Create the vector
vec <- c(5, 3, 6, 9, 12, 6, 3, 2, 9, 10, 36)

# Plot the chart
hist(
vec,
xlab = "Weight", ylab = "Frequency", main = "Histogram of vector",
col = "green", border = "black"
)

Output

### Using the density() function in R to plot

Here, we will use the density() function to plot a graph with the data as an iris dataset. And we will use the ggplot2 package for this example. So, if you don’t have this package, you need to install it.

# Import package
library(ggplot2)

# Using density() function
dens <- density(iris$Sepal.Length) # Plot plot(dens, frame = FALSE, main = "Density", col = "red") Output ### Using the hist() and density() functions in the same frame Now, we will use hist() and density() functions in the same frame to plot a graph and use the iris dataset in this example. Follow the code example below to understand. # Plot with hist() function hist( iris$Sepal.Length,
prob = TRUE,
main = "Histograms and density",
col = "green", border = "black",
xlab = "Temp", ylab = "Density"
)

# Plot with density() function
lines(
density(iris\$Sepal.Length),
lwd = 2, col = "red"
)

Output