What is Data Structures?

 What is Data Structures?

Data Structures could be a representation of logical relationships existing between individual elements of knowledge. In other words, Data Structures define the simplest way of organizing all data items that consider not only the weather stored but also their relationship to every other. The term Data Structures is employed to explain the way data is stored.

To develop a program of an algorithm we should always select appropriate Data Structures for that

algorithm. Therefore, Data Structures is represented as Algorithm + Data Structures = program.

Data Structures is alleged to be linear if their elements form a sequence or a linear list. The linear data

A data

structure is claimed to be non-linear if its elements form a hierarchical classification where data items

appear at various levels.

Trees and Graphs are widely employed in non-linear Data Structures. Tree and graph structures represent

a hierarchical relationship between individual data elements. Graphs are nothing but trees with certain

restrictions removed.

Data Structures Tutorial

 A program might not work of course So as a programmer it's mandatory to decide on the foremost appropriate data built using improper data structures for a program.

The term data means a worth or set of values. It specifies either the worth of a variable or a continuing (e.g., marks of scholars, name of an employee, address of a customer, the worth of pi, etc.). While an information item that doesn't have subordinate data items is categorized as an elementary item, the one that's composed of 1 or more subordinate data items is termed a bunch item. as an example, a student's name is also divided into three sub-items-first names, name, and family name, but his roll number would normally be treated as one item.

A record could be a collection of knowledge items. as an example, the name, address, course, and marks obtained are individual data items. But of these data items is grouped together to create a record.

A file may be a collection of related records. for instance, if there are 60 students in an exceedingly class, then there are 60 records of the scholars. of these related records are stored in a very file. Similarly, we will have a file of all the workers working in a company, a file of all the purchasers of an organization, a file of all the suppliers, so on and then forth.

Moreover, each record in a very file may encompass multiple data items but the worth of a particular Moreover, the info item uniquely identifies the record within the file. Such an information item K is termed a primary key, and therefore the values K, K, ... in such a field are called keys or key values. as an example, in an exceedingly student's record that contains roll number, name, address, course, and marks obtained, the sphere roll number could be a primary key. the remainder of the fields (name, address, course, and marks) cannot function primary keys, since two or more students may have the identical name, or may have the identical address (as they could be staying at the identical place), or is also enrolled within the same course, or have obtained same marks.

Types of Data Structures

• Primitive Data Structures.

• Non-primitive Data Structures.

Primitive Data Structures are the fundamental Data Structures that directly operate upon the machine

instructions. they need different representations on different computers. 


Data Structures. They emphasize grouping the identical or different data items with the connection between

each data item. 


Linear 

Non-linear Data Structures

Linear: If the weather of a knowledge structure are stored in a very linear or sequential order, then it's a linear organisation. 


Representation of Linear Data Structures: Linear data structures may be represented in memory in two other ways. a way is to possess a linear relationship between elements by means of sequential memory locations. the opposite way is to own a linear relationship between elements by means of links. 

Non-Linear Data Structures: If the weather of a knowledge structure aren't stored in sequential order, then it's a non-linear organization. the link of adjacency isn't maintained between elements or non-linear organization.

Examples of Non-Linear Data Structures: Trees and Graphs.

Data Structures Operations:

1. Traversing

2. Searching

3. Inserting

4. Deleting

5. Sorting

6. Merging

1. Traversing- it's wont to access each data item exactly once in order that it is processed.

2. Searching- it's wont to learn the situation of the information item if it exists within the given collection of

data items.

3. Inserting- it's accustomed add a replacement data item within the given collection of information items.

4. Deleting- it's accustomed delete an existing data item from the given collection of knowledge items.

5. Sorting- it's accustomed arrange the info items in some order i.e. in ascending or descending order in

case of numerical data and in dictionary order just in case of alphanumeric data.

6. Merging- it's accustomed combine the information items of two sorted files into one enter the sorted

form.

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