Histogram in Matlab

Introduction to Histogram in Matlab

Histogram is a representation of any statistical information showing the frequency of data items in successive intervals. MATLAB supports plotting histogram feature that enables the user to create a bar graph for any vector or matrix and grouping the data into bins using an automatic binning algorithm. For each bin, the area represents the frequency of occurrence of the data, not the height. It supports customization in histogram presentation.

Syntax:

In earlier versions, hist() and histc() were used to generate histogram plots. In later versions those functions are replaced with new functions with advanced capabilities i.e. histogram(), histcounts() and discretize().

The syntax for the above-recommended functions are as follows:

• histogram(X, a_1,a_2,…..,a_n)
• histcounts(X, a_1,a_2,…..,a_n)
• discretize(X, a_1,a_2,…..,a_n)

Where X: Data input in the form of vector or matrix.

a_1,a_2,…..,a_n: Attribute values (optional)

Creation of Histogram in Matlab: MATLAB makes it a single click action to create a histogram for any data. A histogram can be created by using the inbuilt function histogram().

Example:

The below code is written to generate 100 random numbers and histogram() is used to plot a histogram for the generated data.

Code:

data = randn(100,1);
h = histogram(data)

Output:

Once any histogram object is created, it can be altered by altering its property values, that makes changes in the properties of bins and thus in the display.

Properties of Histogram in Matlab

Various properties that are featured for the histogram in MATLAB, are as follows:

1. Bins

2. Categories

This property allows to plot histogram for each category defined in the input categorical array. If bin count is specified, categories sets the associated category descriptions in the plot.

This property contains parameters such as mentioned below:

3. Data

This value gets distributed over a histogram plot among the bins. This property consists of different parameters such as:

4. Color and Styling

5. Legend

This property in the MATLAB adds descriptive labels to the plots. It comprises of:

6. Interactivity

7. Callbacks

8. Callback Execution Control

9. Parent/Child

10. Identifiers

Examples of Histogram in Matlab

Let’s understand the usage of different attributes referring to various examples given below:

Example #1 – Changing Bin Counts

Code:

data = randn(100,1);
nbins = 10;
h = histogram(data,nbins)

Output:

Example #2 – Changing Bin Width

Code:

data = randn(100,1);
histogram(data,'BinWidth',2)

Output:

Example #3 – Changing Normalization Type

Code:

data = randn(100,1);
h = histogram(data,'Normalization','countdensity')

Output:

Example #4 – Changing Display Style

Code:

data = randn(100,1);
h = histogram(data,'DisplayStyle','stairs')

Output:

Example #5 – Changing Color of the Bars

Code:

data = randn(100,1);
h = histogram(data,'FaceColor','#A2142F')

Output:

A histogram plot lets you to understand and to analyze the set of continuous data under a frequency distribution. It is advantageous over a bar chart as it allows to divide data into classes in terms of bins which helps to do inspection over a specific category of data as required.

Additional Note:

• The function histogram() creates a histogram object having modifiable properties within.
• Histogram() and histcount() have common built-in options, automatic binning and normalization features.
• The primary calculation function for histogram i.e. histcounts() exhibits consistent behavior.
• Discretize() has extended feature about deciding placements of the bin for each element.

Recommended Articles

This is a guide to Histogram in Matlab. Here we discuss the Creation of Histogram in Matlab and its properties along with its examples and Code Implementation. You can also go through our suggested articles to learn more –

1. Introduction to MATLAB Functions
2. Top 10 Advantages of Matlab
3. Overview of Mean Function in Matlab
4. How to Use Matlab? | Operators Used
5. Complete Guide to Matlab stem()