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DATUM DATA
SINGLE VALUE
singular of data
MULTIPLE VALUE
Plural of datum /data
Basic Terminologies
 DATA : Data are simply values or sets of values
 DATA ITEMS: Data items refers to a single unit of values
Group items : Data item divided into sub-items
Ex: Name divided into three - first name, middle
name and last name
Elementary items : Data items that are not able to divide
into sub-items
Ex: PAN Number , Bank account number etc….
 DATA TYPE : Kind of data that may appear in computation
Ex: In C - int, float, char, double, long double, Boolean ,etc.
a=2 ……… integer data type
b=3.5……. Floating data type
c=a………… character data type
 VARIABLE: Variable is a symbolic name given to the value/ data
a=2 ……… a - is a variable name for a data
 ENTITY : Something that has certain attributes ( additional information
about entity ) or properties which may be assigned values.
Ex: Employee of an organization,
Attributes of Employee  Name = John ,Age=23, Gender = Male,
Employee No= 33
 ENTITY SET : Entity with similar attributes ( e.g all employees of an
organization )
 RECORD : Collection of field values of a given entity
Name Age Gender Employee No
John 23 Male 33
Babu 25 Male 34
chitra 22 Female 35
 FIELD: Is a single elementary unit of information representing an attribute
of an entity field
value
 FILE : Collection of records of the entities in a given entity set
 Classification of Records : According to length
1. Fixed-length records : Records contain the same data items with
same amount of space assigned to each data item
2.Variable-length records: file records with different length
Name Age Gender Employee No
John 23 Male 33
Babu 25 Male 34
chitra 22 Female 35
Data Structures-Definition
Data structure is the organization of
the data in a way so that it can be used
Efficiently
TYPE OF DATA STRUCTURE
Primitive Data Types
 Each variable has a specific data type
 It tells - size, range and the type of a value that can be stored in a
variable
 There are 4 basic primitive data types
integer data types, such as short, int, long
floating-point data types, such as float, double
character data type, such as char
Pointer
 Integer data type
allows a variable to store numeric values
The storage size of integer is 2 byte, Ex: a=2
 Character data type
allows a variable to store only one character
Storage size of character data type is 1 byte, Ex: a=g
 Float data type
 allows a variable to store decimal values
Storage size of float data type is 4, Ex: a=2.34
Pointer :
 Special type of variables that are used to store address of
another variable rather than values
This variable can be of type int, char or any other pointer
Non- Primitive Data Types
Based on arrangement , Classification of data structure are
Linear Data structures
Non-Linear Data structures
 Linear Data structures : Arranging the elements in Linear
fashion Ex: Stacks , Queue and Lists
 Non-Linear Data structures: Representing the elements in
Hierarchical order. Ex: Trees ,Graphs
 Linear Data structures : Arranging the elements in sequence fashion
Ex: Name of the students
 Non-Linear Data structures: Representing the elements in
Hierarchical order. Ex: Trees ,Graphs
Anu Abirami Arun Babu Balaji Gowtham
Linear Data structures
 Array- kind of data structure that can store a fixed-size
sequential collection of elements of the same type
 Consider array size 9
LIST
 Linear data structure, Where each node connected together via links –pointer
 But data are not stored at contiguous memory locations
Based on Characteristic , Classification of data structure are
 Static data structure :
 size of the structure is fixed
 The content of the data structure can be modified
 but without changing the memory space allocated to it
Ex : Array size of array is 5
 Dynamic data structure :
size of the structure in not fixed
Can be modified during the operations performed on it
Designed to facilitate change of data structures in the run time
Ex: List
1 2 3 4 5
UNIT 3.pptx-Data Structures definition with examples
DIFFERENCE BETWEEN ARRAY AND LINKED LIST
Arrays linked list
Size of any array is fixed Size of a list is variable
It is necessary to specify size of
array during declaration
It is not necessary to specify
size of list during declaration
Process of Insertion and
deletions is difficult
Process of Insertion and
deletions is easy
It occupies less memory than a
linked list
It occupies more memory –
because it store additional
address field for each data
STACK
 Stack is an ordered collection of elements
 Insertions and deletions are restricted to one end called
top
QUEUE
 Queue is an ordered collection of elements
 Insertions and deletions are restricted to one end
 data are added - rear end [last],deleted - front end [first]
Non-Linear Data structures
TREE
 A tree is a non-linear data structure
 Which represents hierarchical relationship between
individual data items
GRAPH
 A graph is a non-linear data structure
 Data represents less relationship between its adjacent elements.
 There is no hierarchical relationship between the adjacent elements in
case of graphs
Data Structure Operations
Abstract Data Type
An ADT is a collection of data and associated
operations for manipulating that data
It not shows the Implementation part
Basic Operations on Data Structures
 Creation –Creating a new DS
 Insertion − Add a new data in the existing DS
 Deletion − Delete an existing data item from the DS
 Traversal − Access each data item exactly once so that it can be processed
 Searching − Find out the location of the data item if it exists in the DS
 Sorting − Arranging the data items in some order
 Merging: Combining the data items of two files into single file
 Updation: Updating the current value in the DS with some new value
 isEmpty( ): It tests whether the DS is empty
 isFull( ): It tests whether the Memory is Full
 isFirst( ): It returns first element of the data structures
 isLast( ): It returns last element of the data structures
Analysis of an Algorithm
Efficiency
Efficiency of DS is always measured in terms of
TIME and SPACE
An ideal DS that takes
least possible running time and consumes
least memory space
UNIT 3.pptx-Data Structures definition with examples

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UNIT 3.pptx-Data Structures definition with examples

  • 1. DATUM DATA SINGLE VALUE singular of data MULTIPLE VALUE Plural of datum /data
  • 2. Basic Terminologies  DATA : Data are simply values or sets of values  DATA ITEMS: Data items refers to a single unit of values Group items : Data item divided into sub-items Ex: Name divided into three - first name, middle name and last name Elementary items : Data items that are not able to divide into sub-items Ex: PAN Number , Bank account number etc….
  • 3.  DATA TYPE : Kind of data that may appear in computation Ex: In C - int, float, char, double, long double, Boolean ,etc. a=2 ……… integer data type b=3.5……. Floating data type c=a………… character data type  VARIABLE: Variable is a symbolic name given to the value/ data a=2 ……… a - is a variable name for a data
  • 4.  ENTITY : Something that has certain attributes ( additional information about entity ) or properties which may be assigned values. Ex: Employee of an organization, Attributes of Employee  Name = John ,Age=23, Gender = Male, Employee No= 33  ENTITY SET : Entity with similar attributes ( e.g all employees of an organization )  RECORD : Collection of field values of a given entity Name Age Gender Employee No John 23 Male 33 Babu 25 Male 34 chitra 22 Female 35
  • 5.  FIELD: Is a single elementary unit of information representing an attribute of an entity field value  FILE : Collection of records of the entities in a given entity set  Classification of Records : According to length 1. Fixed-length records : Records contain the same data items with same amount of space assigned to each data item 2.Variable-length records: file records with different length Name Age Gender Employee No John 23 Male 33 Babu 25 Male 34 chitra 22 Female 35
  • 6. Data Structures-Definition Data structure is the organization of the data in a way so that it can be used Efficiently
  • 7. TYPE OF DATA STRUCTURE
  • 8. Primitive Data Types  Each variable has a specific data type  It tells - size, range and the type of a value that can be stored in a variable  There are 4 basic primitive data types integer data types, such as short, int, long floating-point data types, such as float, double character data type, such as char Pointer
  • 9.  Integer data type allows a variable to store numeric values The storage size of integer is 2 byte, Ex: a=2  Character data type allows a variable to store only one character Storage size of character data type is 1 byte, Ex: a=g  Float data type  allows a variable to store decimal values Storage size of float data type is 4, Ex: a=2.34
  • 10. Pointer :  Special type of variables that are used to store address of another variable rather than values This variable can be of type int, char or any other pointer
  • 12. Based on arrangement , Classification of data structure are Linear Data structures Non-Linear Data structures  Linear Data structures : Arranging the elements in Linear fashion Ex: Stacks , Queue and Lists  Non-Linear Data structures: Representing the elements in Hierarchical order. Ex: Trees ,Graphs
  • 13.  Linear Data structures : Arranging the elements in sequence fashion Ex: Name of the students  Non-Linear Data structures: Representing the elements in Hierarchical order. Ex: Trees ,Graphs Anu Abirami Arun Babu Balaji Gowtham
  • 15.  Array- kind of data structure that can store a fixed-size sequential collection of elements of the same type  Consider array size 9
  • 16. LIST  Linear data structure, Where each node connected together via links –pointer  But data are not stored at contiguous memory locations
  • 17. Based on Characteristic , Classification of data structure are  Static data structure :  size of the structure is fixed  The content of the data structure can be modified  but without changing the memory space allocated to it Ex : Array size of array is 5  Dynamic data structure : size of the structure in not fixed Can be modified during the operations performed on it Designed to facilitate change of data structures in the run time Ex: List 1 2 3 4 5
  • 19. DIFFERENCE BETWEEN ARRAY AND LINKED LIST Arrays linked list Size of any array is fixed Size of a list is variable It is necessary to specify size of array during declaration It is not necessary to specify size of list during declaration Process of Insertion and deletions is difficult Process of Insertion and deletions is easy It occupies less memory than a linked list It occupies more memory – because it store additional address field for each data
  • 20. STACK  Stack is an ordered collection of elements  Insertions and deletions are restricted to one end called top
  • 21. QUEUE  Queue is an ordered collection of elements  Insertions and deletions are restricted to one end  data are added - rear end [last],deleted - front end [first]
  • 23. TREE  A tree is a non-linear data structure  Which represents hierarchical relationship between individual data items
  • 24. GRAPH  A graph is a non-linear data structure  Data represents less relationship between its adjacent elements.  There is no hierarchical relationship between the adjacent elements in case of graphs
  • 26. Abstract Data Type An ADT is a collection of data and associated operations for manipulating that data It not shows the Implementation part
  • 27. Basic Operations on Data Structures  Creation –Creating a new DS  Insertion − Add a new data in the existing DS  Deletion − Delete an existing data item from the DS  Traversal − Access each data item exactly once so that it can be processed  Searching − Find out the location of the data item if it exists in the DS  Sorting − Arranging the data items in some order
  • 28.  Merging: Combining the data items of two files into single file  Updation: Updating the current value in the DS with some new value  isEmpty( ): It tests whether the DS is empty  isFull( ): It tests whether the Memory is Full  isFirst( ): It returns first element of the data structures  isLast( ): It returns last element of the data structures
  • 29. Analysis of an Algorithm
  • 30. Efficiency Efficiency of DS is always measured in terms of TIME and SPACE An ideal DS that takes least possible running time and consumes least memory space