Boxplot in Matlab

Introduction to Boxplot in Matlab

Boxplot function is used to represent data in a graphical way with respect to the box. It creates a graph of the Boxplot. Depending upon the database and input number of box representation is variable. If there is only one row or column of data available in the input Boxplot function will give only one box. And if data is available in the form of a matrix or in a number of rows as well as columns then the boxplot function will give a number of boxes with respect to the number of columns. In Boxplot always we can see one mark in the middle, that mark represents the median of all input data. The bottom side of the box shows a twenty-five percent database proportion a topside or edge shows seventy-five percent database proportion.

Syntax:

Boxplot (var1)

Boxplot (var1,var2)

Boxplot ( user-defined parameters)

How does Boxplot Calculate in Matlab?

Let us discuss the steps to calculate Boxplot.

Step 1: Accept database (load command)

Step 2: Sort the data in descending or ascending order

Step 3: Find the median of all the values

Step 4: Mark on rough line

Step 5: Create three quartiles on rough line

Step 6: Draw a horizontal line by joining quartiles

Step 7: Display final plot

Examples of Boxplot in Matlab

Given below are the examples of Boxplot in Matlab:

Example #1

Consider one example of an inbuilt database of cars. ( “car small” ) in this database acceleration, origin all this information is available. we can create a Boxplot by assigning any value parameter from the above options. Let us consider the acceleration parameter. There are 100 entries of acceleration, so we can plot a graph of acceleration with respect to all vehicles. In this case, we are considering only one parameter which is acceleration that is why we will get only one box in output.

Code:

clear all ;
clc ;
load carsmall
boxplot (Acceleration)
xlabel ( 'All Vehicles' )
ylabel ( 'Acceleration' )
title ( 'Acceleration for All Vehicles' )

Work space:

(Database values of acceleration for example 1, example 2 and example 3)

12 11.50 11 12 10.50 10 9 8.50 10 8.50 17.50 11.50 11 10.50 11 10 8 8 9.50 10 15 15.50 15.50 16 14.50 20.50 17.50 14.50 17.50 12.50 15 14 15 13.50 18.50 15.50 16.90 14.90 17.70 15.30 13 13 13.90 12.80 15.40 14.50 17.60 17.60 22.20 22.10 14.20 17.40 17.70 21 16.20 17.80 12.20 17 16.40 13.60 15.70 13.20 21.90 15.50 16.70 12.10 12 15 14 19.60 18.60 18 16.20 16 18 16.40 20.50 15.30 18.20 17.60 14.70 17.30 14.50 14.50 16.90 15 15.70 16.20 16.40 17 14.50 14.70 13.90 17.30 15.60 24.60 11.60 18.60 19.40

Output:

Example #2

Now let us consider we wish to plot with respect to two parameters so if there is more than one parameter we will get multiple boxes at the output. In this example, we consider two parameters acceleration and origin. At the output we can see separate boxes for each origin (country – France, USA, Japan, Germany, Sweden, and Italy).

Code:

clear all ;
clc ;
load carsmall
boxplot (Acceleration ,Origin)
title ( 'Acceleration by Vehicle Origin' )
xlabel ( 'Origin')
ylabel ( 'Acceleration' )

Output:

Example #3

In the third example, here we use two parameters, these parameters are not inbuilt parameters. Here we use user-defined parameters. To create parameter here default range is assigned then rand operation is used to create the first parameter. And the second parameter is created by using repmat function. Repmat function is used for array manipulations, so three arrays or vectors are used in the second parameter. These two user-defined parameters are var 1 and var 2.

Code:

clear all ;
clc ;
rng ( 'default' )
v1 = rand (3 , 1) ;
v2 = rand (6 , 1) ;
v3 = rand (9 ,1) ;
var1 = [ v1 ; v2 ; v3] v4 = repmat ({ '1' } ,3,1) ;
v5 = repmat ({ '2' } ,6,1) ;
v6 = repmat ({ '3' } ,9,1) ;
var2 = [ v 4 ; v 5 ; v 6 ] ;
boxplot ( var1 ,var2)

Command window:

var1 =

0.8147    0.9058   0.1270   0.9134   0.6324   0.0975   0.2785   0.5469   0.9575   0.9649   0.1576   0.9706   0.9572   0.4854   0.8003   0.1419   0.4218   0.9157

Output:

Conclusion

In this article, we have seen how to create a box plot by using the database. While creating a box plot we can change box colors, box outline size, median style, plot size, plot style, notch status, etc. By using a box plot we can represent the database very efficiently.

This has been a guide to Boxplot in Matlab. Here we discuss the introduction, examples and how does Boxplot calculate in Matlab. You may also have a look at the following articles to learn more –

1. Contour plot in Matlab
2. List of R Packages
3. Matrix Multiplication in Matlab
4. Column Vector Matlab