Overview of Data Types in MATLAB
In this data types in MATLAB article, we shall provide a very basic introduction to MATLAB and would mainly talk about its data types. MATLAB is one of the most famous software tools for numeric programming and is widely used across the world. It is developed by MathWorks and probably the most favorite software tool in academics and research purposes. MATLAB is used in almost all colleges and universities for higher education in science, technology, and engineering field. MATLAB is proprietary which means that one needs to purchase a license for using it.
Still compared to many other similar opensource technologies, MATLAB is quite market dominating and is well known for its faster execution speed, a vast set of libraries that support a huge domain of science and engineering and accuracy and reliability in its computation. The goal of this article would be to introduce MATLAB to its firsttime user and make them familiarize with various simple knowhow of using it.
MATLAB has the following 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
 Numeric Types: – Under this type comes Integer and floatingpoint or fraction data
 Characters and Strings: – Text are represented in character arrays and string arrays
 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.
 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 nonnumeric.
 Tables: – Arrays are represented here in a tabular form whose named columns may contain different types such as numeric, categorical, etc.
 Timetables: – Timestamped data such as DD/MM/YYYY/HR/MIN/SEC in tabular form.
 Structures: – Most versatile as well as complex, this type contains arrays with named fields that contain varying types and sizes.
 Cell Arrays: – This again is a data type where an array can contain data of variable types and sizes.
 Function Handles: – Such data types allow variables to call a function indirectly.
 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.
 Time Series: – time series data has a specific type where data vectors are sampled over the time period.
 Data Type Identification: – Such data types help us determine the data type of any variable.
 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 singleprecision numeric data 
Double  This is doubleprecision 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 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 userdefined class 
Java classes  Such types represent objects which are constructed from a Java class. 
Examples: –
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 doubleprecision 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 doubleprecision 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 programing language. Each of these data types is very important and MATLAB users need to deeply understand the property and usages of each of this type 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 –
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