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Introduction to Data Structures
Neso Academy
From this presentation onwards,, we will study a new subject that is,
data structures
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, I will introduce what data
structure is and some real-life examples of data structure
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This is what data is
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data structure gives us the way to structure the data, to
appropriately manage the data
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This is the reason, why
companies are preferring this subject over other subjects because this is
very important subject
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You know that this is the
famous
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one such application is Google
Docs,, or power, Point, or microsoft word
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now, let 's discuss some real-life examples of data
structures
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I press control Z, this element gets selected and you
know, it will get poped out of the stack and will get placed within this
redo stack
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, stack is our data structure
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data structures are useful in day to day life and
we using them more frequently, and that is why, it is so hot in it
industry
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we can use graph data structure to store information like
this
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Data Types vs
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A data type defines a certain domain of values but also defines what
operations are allowed on those values
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ADTs are like user defined data types
which defines operations on values using functions without specifying
what is there inside the function and how the operations are performed
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There are multiple ways to implement an
ADT
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The
program which uses data structure is called a client program
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The implementation can
go on without affecting the stack program
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Abstract data type provides abstraction which means hiding details
from the user and it is very important because user does n't bother
about how that particular thing is implemented
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So, this separation is required
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Data Structure Definition & Advantages
Neso Academy

In this presentation, we will discuss the formal definition of data
structures and discuss some of the advantages of it
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When I say efficiently, it means in terms of time
as well as space
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But how to know which data
structure to use for a particular ADT? That is the basic question
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ADT is the blueprint , while
data structure is the implementation
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The client program does n't have to worry
about what is going inside
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Types of Data Structures
Neso Academy

A data structure is linear when all the elements are arranged
in a linear order or sequential order
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We have a non-linear data structure, we
have static data structures and dynamic data structures
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The advantage of such data structure is that
we can access data very fast
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We will discuss this later that how linked list can be
created
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Basics of Asymptotic Analysis (Part 1)
Neso Academy
A data structure is the organization of the data in a way so that it can
be used efficiently
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And we want to
perform some operations on it
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An ideal data
structure could be the one that takes the least possible time for all its
operations and consumes the least memory space
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The size of the array is not
defined
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And right now, we have eight elements in this array
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Then, we can easily add our element at the beginning of the
list
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Inserting a data structure is much efficient in
adding data in comparison to the array
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Study time complexity is very important
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Okay friends,
this is it for now
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Back to the
page you came from the bottom of the page
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Basics of Asymptotic Analysis (Part 2)
Neso Academy
WE have learnt that on the basis of operations performed on

data structures, we could be able to compare the time
complexity of the data structures
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? Let 's tackle this question by using some
methods
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Exact running time calculation is not
at all practical--let me tell you it is not practical
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structure is giving the best performance on the
other input size

Basics of Asymptotic Analysis (Part 3)
Neso Academy
Examining the exact running time is not the best solution to calculate
the time complexity that 's what we have learned from the last lecture
right
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running time generally
depends on the size of the input that what is going to be the running
time
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[UNK]
represents the number of instructions executed for the input value N
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Denotes the time complexity
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complexity
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time a particular operation will
take in a particular machine
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We just have to put
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This becomes 6
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Percentage of time is 21 point seven four percent
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Obviously this
we are calculating for n equal to one
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For larger values of n
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As you are increasing the value of N
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If we can
eliminate the rest of the terms as they are not contributing much to the
time
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If we take F n is equal to five and
squared
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IT gives us the upper
bound on a function by which we can make sure that the function will
never grow faster than this upper bound
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We are not interested
in the exact running time
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THis
is the upper bound on this function, which simply says that this function
will never grow faster than this
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It means, that we are actually
calculating the worst case time complexity
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Four n plus three is not less than or equal to n
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We need to find the growth rate of this function is linear
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IT
is not the case that is suddenly it will behave like a quadratic function
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And we can clearly see from this function as
well
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f ( n)
equal to big O of n
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Now, let 's analyze the growth rate visually
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This purpose, I have
created this table with different n values
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Here also, we will see some examples
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So, let 's
get started
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IT
gives the least upper bound on the function, which gives the surety that
the function under consideration will never grow faster than this upper
bound
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SO,
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This G ( N) is basically representing the upper
bound on F (n)
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WE use these standard functions for least upper bound on a particular
function under consideration
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While two
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Basically, we usually
put them in place on G ( n ) SO, we can use log n base 2, n square, n
cube, n cube and n square to get big O of n square
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WE are interested in finding the
growth rate of this function
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The growth can be linear only because the highest term here
you can see is n
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The algorithm
written by you for calculating the sum of first n natural numbers is the
fastest among all
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has written an algorithm
which has a linear growth
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With Big O notation
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Different programs
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You can clearly say that
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Okay
friends, this is it for now
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