DS----Data Structure unit 1.1

What is Data Structure?

A data structure is a way of organizing and storing data in a computer so that it can be accessed and manipulated efficiently. It defines the layout and organization of data in a particular way, which can improve the efficiency of operations like searching, sorting, and updating the data. Examples of common data structures include arrays, linked lists, trees, and hash tables.

Types of Data Structures

1.Primitive data structure

2.Non-primitive data structure

1.Primitive data structure

Primitive data structures are basic data structures that are directly supported by most programming languages. These data structures are usually built into the language and have a fixed size and format. Examples of primitive data structures include:

1.Integers (whole numbers)
2.Floating-point numbers (real numbers)
3.Characters (single letters or symbols)
4.Booleans (true or false values)

Primitive data structures are often used as building blocks for more complex data structures, and are essential for performing basic operations in programming.

2.Non-primitive data structure

The non-primitive data structure is divided into two types:
1.Linear data structure
2.Non-linear data structure

Non-primitive data structures are more complex data structures that are composed of one or more primitive data types, as well as other non-primitive data types. Non-primitive data structures are typically not built into programming languages, and must be implemented using primitive data types and programming constructs. Examples of non-primitive data structures include:

1.Arrays
2.Linked lists
3.Stacks
4.Queues
5.Trees
6.Graphs
7.Hash tables
8.Heaps
9.Tries
10.Sets
11.Maps
12.Strings

Non-primitive data structures are often used to represent complex data relationships and perform advanced operations, such as searching and sorting.

Algorithms

An algorithm is a step-by-step procedure or set of rules that a computer follows to solve a problem or perform a task. Algorithms are fundamental to computer science and are used in a wide range of applications, including search engines, recommendation systems, data analysis, and machine learning. The efficiency of an algorithm can have a significant impact on the performance of a program, and there are various techniques for analyzing and optimizing algorithms. Some common algorithm design techniques include divide and conquer, dynamic programming, and greedy algorithms.

Static data structure

A static data structure is a data structure with a fixed size that cannot be modified once it is created. The size of the structure is determined at the time of its creation and remains the same throughout its lifetime.

Arrays are the most common example of a static data structure, as the size of an array is determined when it is declared, and the number of elements in the array cannot be changed during runtime.

Other examples of static data structures include fixed-size buffers, static queues, and static stacks. These data structures are simple and efficient, but their fixed size can limit their flexibility and scalability.

Static data structures are useful in situations where the maximum size of the data set is known in advance and remains constant. They are often used in embedded systems, where memory is limited and predictable, and dynamic memory allocation may not be possible or desirable.

Dynamic data structure

A dynamic data structure is a data structure that can change size during runtime. The size of a dynamic data structure is not fixed, and it can grow or shrink as needed to accommodate new elements or remove existing ones.

Some common examples of dynamic data structures include dynamic arrays, linked lists, binary trees, hash tables, and graphs. These structures can be expanded or contracted as needed, making them more flexible and adaptable than static data structures.

Dynamic data structures are useful when the size of the data set is not known in advance or can change frequently. They are commonly used in database systems, operating systems, and software applications where data is created, modified, and deleted dynamically. The dynamic nature of these structures allows for efficient memory usage and optimization of the data access and manipulation.

Note This are comman operating

Searching: We can search for any element in a data structure.
Sorting: We can sort the elements of a data structure either in an ascending or descending order.
Insertion: We can also insert the new element in a data structure.
Updation: We can also update the element, i.e., we can replace the element with another element.
Deletion: We can also perform the delete operation to remove the element from the data structure.

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