Do
you want to gain knowledge about data structure and the various types of data structures? If yes,
congratulations you are in the right place. In this article, we will be dealing
with the same.
What is Linear Data Structure?
Data
structures are the in-depth concept of Software Development. The linear data structure is usually
associated with computer science. Users use this structure for organizing,
managing & stockpiling data format for systematic access and revision.
The
computer; we use for several purposes; works on computer programs. These
programs are directly dependent on the huge volume of data for performance.
Here comes the need to arrange the data. And this arrangement of data in an
organized system is defined as a data structure.
Today,
linear data structures are utilized to organize bulky data while
categorizing/indexing services. Precisely speaking, data structures are routes
to well-organized and logical algorithms. The primary purpose of forming a
linear data structure is to minimize the space and reduce the time complicacy
of different tasks.
Now
that you are well aware of the definition of linear data structure lets dive deep into the various types of linear data structure.
List of the linear Data Structure examples
1. Array
The
array is one of the types of linear data structures that accumulate elements at
memory locations. All the elements stores are contiguous in type. You can
understand an array as a structure that stores invariable objects in a proper
sequence.
The
plan or scheme by which an array is formed is to store numerous data of the
same type altogether. The 1st thing to be decided here is the size
of the array; only then can one store the data. In an array, one can easily
access or modify a particular element stored as per their locations.
You
can understand the array with the help of an example: Suppose there are 100
patients in a hospital, then the size of the array has to be mentioned as 100.
The age of all the students can then be stored in the created array. Here you
need not create distinct variables for the ages of every patient. A simple
traversal of the array will be enough to access its elements.
2. Stack
A
stack is a data structure where the elements are arranged in such a manner that
it follows up the LIFO principle. LIFO means last-in-first-out. Hence, in a
stack, the last element stored will be removed first. Stack is often federated
with 2 types of operations i.e. push and pop. Push adding of an element &
POP removing the last element. You can understand the stack by means of an
example: Suppose there is a heap of coins and the last coin kept on the pile is
removed first.
3. Queue
While
talking about the types of linear data
structures, one has to include Queue Data Structure. Unlike a stack that
works in the LIFO (last-in-first-out) manner, queue data structure works in the
FIFO (first-in-first-out) principle. Here, in the queue data structure, the
first element stored in the queue has to be initially removed. You can
understand queue data structure with the help of an example: Suppose a queue of
people in the bus stand; then the first person in the queue will enter the bus
first followed by others.
4. Linked list
The
linked list is another classification of data structure. Here, the user stores
separate objects in a proper sequence. Every single object stored in the data
structure will have the data and a reference to the succeeding object. A linked
list has a head the 1st element of the linked list. It also has
a null the final node of the linked list.
A
linked list differs from the other 3 types of data structures mentioned above.
The primary differences can be illustrated based on memory allocation, internal
structure, and the operations executed on the linked list.
In
an array, one can easily get on to any particular element; but in a linked list
its much more tough & slow. It is because the indexing process in a linked
list begins from the head and navigates through the entire structure until a
particular element is reached. However, a linked list has an advantage over
other types of data structures; i.e. adding or deleting elements can be done at
the beginning very swiftly.
Final Takeaway
All
in all, we can say that enormous data size is a prerequisite for the proper use
of data structures in computer programs. You can opt for any of the 4 types of
data structures while working on a computer program. Always remember, organized
data enhances the performance of tasks over the elements. If you are interested
to know more about each type of linear data structure, opt for a data science course available easily online.
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