Data Structures is a very complex and vast topic, without some basics concepts overview one can easily get lost and find difficulties in Data Structures.
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- Disclaimer
- This is more like a well written note than a article. Everything here is simplified from references only for the purpose of learning and easier understanding. One should not take this as their sole guide to any exam. If you find any correction/improvement please comment below.
Topic 1: Data and Information
What is Data ?
A data is single unit value - elementary or groups. Data is collection of raw and unorganized facts that needs to processed. Data can be something simple and random and meaning less.
Example: Each person's salary is a single piece of data.
What is Information
When the data is processed, organized, structured in an appropriate sequence and give us a meaning and makes it useful. This meaning is called as Information.
Example: The mean value of people's salary in a particular area is information that can be derived from the given data.
Topic 2: Data Structure and Classification of Data Structures
What is Data Structure?
A data structure is a systematic way of organizing and accessing data. A data structure tries to structure data in way to help us understand how data are stored in a computer and to learn how to organize data for efficient storage and manipulation.
The Data structure can also be defined as a mathematical or logical model, which relates to a particular organization of different data elements.
Data structures provide a means to manage large amounts of data efficiently for uses such as large databases and internet indexing services.
Efficient data structures are key to designing efficient algorithms
Classifications of Data Structures
The classification of Data Structures mainly consists of two categories:
1. Primitive Data Structure
2. Non-primitive data structure
Topic 3: Primitive and Non-primitive Data Structure
Primitive Data Structure
- Primitive Data Structure are also known as simple data structures. A primitive data structure represents the standard data type of a programming language. They can be directly operated by the machine instructions. Examples
- Integer
- Float
- Boolean
- Character
- Pointer
Non-primitive Data Structure
- Non-primitive data structure are also known as compound data structures. These data structures are created with help of primitive data structure. The non-primitive data structure is responsible for organizing the group of homogeneous and heterogeneous data elements. Examples
- Arrays
- Linked Lists
- Stacks
- Graphs
- Non-primitive data structure can further be classified into two categories:
- Linear Data Structures
- Non-Linear Data Structures
- Linear Data Structures consist of:
- Arrays
- Linked Lists
- Stacks
- Queues
- Non-linear Data Structures consist of:
- Trees
- Graphs
Topic 4: Abstract Data Types
Abstract Data Type (ADT) is a logical term where as Data structure is real.
ADT provides the definition of a data type that defines the possible values and operation which can be performed on it.
Suppose an Integer as ADT, by the definition of integers it provides us possible values from -∞ to +∞ and possible operations such addition,subtraction,division and multiplication, these integer values are independent of how the computer stores integer in the memory. The process of providing only the essentials and hiding the details is known as abstraction.
Abstract Data Types were introduced to reduce the complexity from the program making it more flexible, easy to understand and reusable code.
Example: Just abstract it.
Topic 5: Data Structure vs File Organization
A file is used to store information, the information inside the file consist of records or lines. Files are stored and handled on permanent memory location i.e Hard Drive where Data Structure is about storing data or handling data into RAM or temporary memory.
Data Structures are alive till the program is alive, file structures are data structures when a program accesses formatted files because they end up reading them into RAM and navigating in them just as they do with data structures in memory.
Topic 6: Operations of Data Structure
The basic operations that are performed on data structures are as follows:
- Insertion: Insertion means addition of a new data element in a data structure
- Deletion: Deletion means removal of a data element from a data structure if it is found
- Searching: Finding the location of a particular record with a given key value
- Traversal: Traversal of data structure means processing all the data elements present in it.
- Sorting: Arranging data elements of a data structure in a specified order is called sorting.
- Merging: Combining elements of two similar data structures to form a new data structure of the same type or Combining the record in two different sorted files into a single sorted files.
What is Data ?
A data is single unit value - elementary or groups. Data is collection of raw and unorganized facts that needs to processed. Data can be something simple and random and meaning less.
Example: Each person's salary is a single piece of data.
What is Information
When the data is processed, organized, structured in an appropriate sequence and give us a meaning and makes it useful. This meaning is called as Information.
Example: The mean value of people's salary in a particular area is information that can be derived from the given data.
Topic 2: Data Structure and Classification of Data Structures
What is Data Structure?
A data structure is a systematic way of organizing and accessing data. A data structure tries to structure data in way to help us understand how data are stored in a computer and to learn how to organize data for efficient storage and manipulation.
The Data structure can also be defined as a mathematical or logical model, which relates to a particular organization of different data elements.
Data structures provide a means to manage large amounts of data efficiently for uses such as large databases and internet indexing services.
Efficient data structures are key to designing efficient algorithms
Classifications of Data Structures
The classification of Data Structures mainly consists of two categories:
1. Primitive Data Structure
2. Non-primitive data structure
Topic 3: Primitive and Non-primitive Data Structure
Primitive Data Structure
- Primitive Data Structure are also known as simple data structures. A primitive data structure represents the standard data type of a programming language. They can be directly operated by the machine instructions. Examples
- Integer
- Float
- Boolean
- Character
- Pointer
- Non-primitive data structure are also known as compound data structures. These data structures are created with help of primitive data structure. The non-primitive data structure is responsible for organizing the group of homogeneous and heterogeneous data elements. Examples
- Arrays
- Linked Lists
- Stacks
- Graphs
- Non-primitive data structure can further be classified into two categories:
- Linear Data Structures
- Non-Linear Data Structures
- Linear Data Structures consist of:
- Arrays
- Linked Lists
- Stacks
- Queues
- Non-linear Data Structures consist of:
- Trees
- Graphs
Topic 4: Abstract Data Types
Abstract Data Type (ADT) is a logical term where as Data structure is real.
ADT provides the definition of a data type that defines the possible values and operation which can be performed on it.
Suppose an Integer as ADT, by the definition of integers it provides us possible values from -∞ to +∞ and possible operations such addition,subtraction,division and multiplication, these integer values are independent of how the computer stores integer in the memory. The process of providing only the essentials and hiding the details is known as abstraction.
Abstract Data Types were introduced to reduce the complexity from the program making it more flexible, easy to understand and reusable code.
Example: Just abstract it.
Topic 5: Data Structure vs File Organization
A file is used to store information, the information inside the file consist of records or lines. Files are stored and handled on permanent memory location i.e Hard Drive where Data Structure is about storing data or handling data into RAM or temporary memory.
Data Structures are alive till the program is alive, file structures are data structures when a program accesses formatted files because they end up reading them into RAM and navigating in them just as they do with data structures in memory.
Topic 6: Operations of Data Structure
The basic operations that are performed on data structures are as follows:
Abstract Data Types were introduced to reduce the complexity from the program making it more flexible, easy to understand and reusable code.
Example: Just abstract it.
Topic 5: Data Structure vs File Organization
A file is used to store information, the information inside the file consist of records or lines. Files are stored and handled on permanent memory location i.e Hard Drive where Data Structure is about storing data or handling data into RAM or temporary memory.
Data Structures are alive till the program is alive, file structures are data structures when a program accesses formatted files because they end up reading them into RAM and navigating in them just as they do with data structures in memory.
Topic 6: Operations of Data Structure
The basic operations that are performed on data structures are as follows:
- Insertion: Insertion means addition of a new data element in a data structure
- Deletion: Deletion means removal of a data element from a data structure if it is found
- Searching: Finding the location of a particular record with a given key value
- Traversal: Traversal of data structure means processing all the data elements present in it.
- Sorting: Arranging data elements of a data structure in a specified order is called sorting.
- Merging: Combining elements of two similar data structures to form a new data structure of the same type or Combining the record in two different sorted files into a single sorted files.
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