Data Types in MATLAB

Overview of Data Types in MATLAB

Data Types in MATLAB are the supported data formats that are used for computation. MATLAB is a popular mathematical and statistical data analysis tool that has a wide range of features for computation. The various types of data type MATLAB supporting are numeric types, characters, strings, date and time, categorical arrays, tables, timetables, Structures, Cell Arrays, Functional Handlers, Map Containers, Time series, Data type Identification, Data type conversion. Each of the data types accepts and processes a certain type of data format through the variables. MATLAB provides the functionalities to convert one data type to another compatible data type using the conversion functions

Data Types in MATLAB

Following are the Data Types:-

• Numeric Types
• Characters and Strings
• Date and Time
• Categorical Arrays
• Tables
• Timetables
• Structures
• Cell Arrays
• Functional Handles
• Map Containers
• Time Series
• Data Type Identification
• Data Type Conversion

Let’s see the significance of the individual Data Types in MATLAB in details-

1. Numeric Types: Under this type comes Integer and floating-point or fraction data
2. Characters and Strings: Text are represented in character arrays and string arrays
3. Dates and Time: This contains arrays of date and time values which can be again shown in many different formats such as DD/MM/YYYY or MM/DD/YY etc.
4. Categorical Arrays: Under this comes arrays of qualitative data such as a list with values from a finite set of discrete sampled or data of the type non-numeric.
5. Tables: Arrays are represented here in a tabular form whose named columns may contain different types such as numeric, categorical, etc.
6. Timetables: Time-stamped data such as DD/MM/YYYY/HR/MIN/SEC in tabular form.
7. Structures: Most versatile as well as complex, this type contains arrays with named fields that contain varying types and sizes.
8. Cell Arrays: This again is a data type where an array can contain data of variable types and sizes.
9. Function Handles: Such data types allow variables to call a function indirectly.
10. Map Containers: Similar to the dictionary in many languages, such data types have objects with keys where the key is indexed to values, where keys need not be integers.
11. Time Series: Time series data has a specific type where data vectors are sampled over the time period.
12. Data Type Identification: Such data types help us determine the data type of any variable.
13. Data Type Conversion: Using such types, we can convert between many data types such as numeric arrays, cell arrays, character arrays, structures, function handles, and tables, etc.

Now let’s look into each type with more details

Data Types	Definition
Int8	This is called 8 bits signed integer
Uint8	This is 8 bits unsigned integer
Int16	16 bits signed integer
Uint16	16 bits unsigned integer
Int32	32 bits signed integer
Uint32	32 bits unsigned integer
Int64	64 bits signed integer
Uint64	64 bits unsigned integer
Single	This is called single-precision numeric data
Double	This is double-precision numeric data
logical	The logical value of 0 or 1 represents true or false
char	Character data such as alphabets
Cell array	an array of indexed cells where each cell is capable of storing an array of the same or different dimensions and different data type
structure	This is more like a C structure where each structure has a named field which is capable of storing an array of different size or dimension and different data types
Function handle	This acts as a pointer to a function
User classes	Such data types represent objects which are constructed from a user-defined class
Java classes	Such types represent objects which are constructed from a Java class.

Examples

Below is the example

Code:

strg = 'Hello MATLAB!'
n = 234510
dbl = double(n)
unt = uint32(7891.50)
rrn = 15678.92347
cons = int32(rrn)

Output: –

strg = Hello MATLAB!n = 234510dbl = 234510unt = 7901rrn = 15678.9cons = 15679

• In the above example, strng is string data type, n is numeric data type, dbl is double data type, unt is 32 bit unsigned integer, rrn is fractional data which is converted to int 32 integer and stored as cons.

Conversion of Data Types in MATLAB

Function	Purpose
char	This function converts from to character array (string)
int2str	This function converts from integer data to the string
mat2str	This function converts from a matrix to string
num2str	This function converts from number to string
str2double	This function converts from string to double-precision value
str2num	This function converts from string to number
native2unicode	This function converts from numeric bytes to Unicode characters
unicode2native	This function converts from Unicode characters to numeric bytes
base2dec	This function converts from base N number string to decimal number
bin2dec	This function converts from binary number string to decimal number
dec2base	This function converts from decimal to base N number in string
dec2bin	This function converts from decimal to binary number in string
dec2hex	This function converts from decimal to hexadecimal number in string
hex2dec	This function converts from hexadecimal number string to decimal number
hex2num	This function converts from hexadecimal number string to double-precision number
num2hex	This function converts from singles and doubles to IEEE hexadecimal strings
cell2mat	This function converts from cell array to numeric array
cell2struct	This function converts from cell array to structure array
cellstr	This function creates a cell array of strings from a character array
mat2cell	This function converts from array to cell array with potentially different sized cells
num2cell	This function converts from array to cell array with consistently sized cells
struct2cell	This function converts from structure to cell array

Conclusion

• From the above discussion and example, we got a deep look into the various data types of MATLAB programming language. Each of these data types is very important and MATLAB users need to deeply understand the property and usages of each of these types to write efficient MATLAB programs that are fast, optimized for performance, and scalable for future needs.
• As a beginner, users are advised to practice a lot of these syntaxes so that they can understand their usages and relative advantages and disadvantages. Such coding practice is important to have great control over any language and to be able to write efficient MATLAB codes.

Recommended Articles

This has been a guide to Data Types in MATLAB. Here we discuss the introduction, list, and conversions of data types in MATLAB with an example. You can also go through our other suggested articles to learn more –

1. Matlab Operators
2. Getting Started with Applications of Matlab Commands
3. Career in MATLAB
4. MATLAB Interview Questions
5. Matlab Compiler | Applications of Matlab Compiler