The document provides an extensive introduction to programming with Python, highlighting its accessibility and wide usage across various applications such as web development and data analysis. It covers fundamental concepts like data types, operators, functions, object-oriented programming, and control flow structures including loops and conditionals. Additionally, it discusses practical tools such as Jupyter IDE and important Python features such as list comprehensions and built-in functions.

1. CAREERERA
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A warm welcome to Careerera family

2. CAREERERA
®
Introduction to Programming using Python
2

3. WHAT IS PYTHON
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• Python is a popular programming language.
• It was created by Guido van Rossum, and released in
1991.
• It is used for:
⮚web development (server-side).
⮚ software development.
⮚mathematics.
⮚ system scripting.

4. WHY PYTHON IS WIDELY USE?
4
• The python language is one of the most accessible programming
languages
• Due to its ease of learning and usage, python codes can be easily
written and executed much faster than other programming
languages.
• Python works on different platforms (Windows, Mac, Linux etc).
• Python has a simple syntax.
• Python is easy to code.
• Python runs on an interpreter system, meaning that code can be
executed as soon as it is written.
• Python is a object Oriented Programming Language

5. DATA TYPES -NUMBERS
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• Number data types store numeric values. They are immutable data
types, means that changing the value of a number data type results
in a newly allocated object.
• Number objects are created when you assign a value to them.
For example :−
var1 = 10
var2 = 30

6. BOOLEAN
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• Python boolean type is one of the built-in data types provided by
Python, which are defined by the True or False keywords.
• The bool() method is used to return or convert a value to
a Boolean value i.e., True or False, using the standard truth testing
procedure.

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• Strings are arrays of bytes representing Unicode characters.
However, Python does not have a character data type, a single
character is simply a string with a length of 1. Square brackets
can be used to access elements of the string. individual
characters of a String can be accessed by using the method of
Indexing.
For Example:-
value = “Careerera”
STRINGS DATATYPES

8. CONCATENATION IN PYTHON
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Concatenating means obtaining a new string that contains
both of the original strings. You can use “+” operator to
concatenate strings in python.
For Example:-

9. 9
Subset - A set of which all the elements are contained in
another set.
• The issubset() method returns True if all elements of a
set are present in another set (passed as an argument).
• If not, it returns False.
• For Example :-
SUBSET IN PYTHON

10. 10
Position: The index() method returns the index position
of the first occurance of the specified item.
Raises a ValueError if there is no item found.
For Example:
Syntax:
list.index(element, start, end)
USES OF POSITION

11. VARIABLES
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• Variables are reserved memory locations to store values. This
means that when you create a variable you reserve some
space in memory.
• Based on the data type of a variable, the interpreter allocates
memory and decides what can be stored in the reserved
memory.
• Therefore, by assigning different data types to variables, you
can store integers, decimals or characters in these variables.

12. BASIC PROGRAMMING SYNTAX
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• Python syntax are very much simple and easy.
• Every programming language has its own set of rules that make
up its basic syntax.
• Hence ,it’s easy to code in Python.
• For Example:
print(“ Learn from Careerera “)
The syntax mention above is the basic syntax of python
programming language to print .

13. HELLO WORLD PROGRAM IN PYTHON
For example :
13

14. INTEGRATED DEVELOPMENT ENVIRONMENT(IDE) FOR PYTHON
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• Jupyter IDE can be use for python coding.
• Jupyter is a free, open-source, interactive web tool that allows
editing and running files via a web browser.
• To launch a Jupyter notebook, open your terminal and navigate to
the directory where you would like to save your notebook.
• Then type the command Jupyter notebook and the program will
instantiate a local server at localhost:8888

15. DATA STRUCTURE
• Data structures are “containers” that organize and
group data according to type.
• The basic Python data structures in Python include
• list, array, tuples, and dictionary.
• Each of the data structures is unique in its own way.

16. LIST IN PYTHON​
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• Lists are used to store multiple items in a single variable.
• List items are ordered, changeable, and allow duplicate values.
• The elements in a list are indexed according to a definite sequence .
• Indexing starts from 0,1,2,3 so on..
• items in a list need not be of the same type.

17. SYNTAX AND EXAMPLES OF LIST
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Syntax:
Li=[] # empty list
Li1=[1,2,34,5] # list containing element’s
List Example:

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• A tuple is a collection of objects which is ordered and immutable.
• Tuples are ordered, it means that the items have a defined order,
and that order will not change.
• Tuples are written with round brackets.
• tuples allow duplicate values.
• Tuples items can be indexed .
TUPLE IN PYTHON

19. SYNTAX AND EXAMPLES OF TUPLES
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• Syntax:
• a=(1,5,8,9)
• B=(True , False , True)
• Tuple Example:

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• Sets are used to store multiple items in a single variable.
• A set is a collection which is unordered
• Unordered means that the items in a set do not have a defined
order.
• Sets are unchangeable, meaning that we cannot change the
items after the set has been created.
• Sets are unindexed
• Sets are written with curly brackets.
SET IN PYTHON

21. SYNTAX AND EXAMPLES OF SETS
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Syntax:
• a={“Apple” , “Orange” , “Banana” }
Set Example:

22. 22
• Dictionaries are used to store data values in key:value pairs.
• A dictionary is a collection which is ordered*, changeable and
does not allow duplicates.
• Dictionary holds a pair of values
• Dictionary can also be created by the built-in function dict().
• An empty dictionary can be created by just placing to curly
braces{}.
DICTIONARIES IN PYTHON

23. SYNTAX AND EXAMPLES OF DICTIONARIES
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Syntax:
• a={“keys “ :”values”, “keys “ :”values”}
Dictionary Example:

24. OPERATORS
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• Operators are used to perform operations on values and
variables in Python.
• These are standard symbols used for the purpose of logical and
arithmetic operations.
• The value that the operator operates on is called the operand.

25. TYPES OF ARITHMETIC OPERATORS
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• Arithmetic operators are used to perform mathematical operations like
addition, subtraction, multiplication and division.
There are 7 arithmetic operators in Python :
1. Addition
2. Subtraction
3. Multiplication
4. Division
5. Modulus
6. Exponentiation
7. Floor division

26. 26
1. Addition Operator : In Python, + is the addition
operator. It is used to add 2 values.
Example :
ADDITION OPERATORS

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2 . Subtraction Operator : In Python, (– )is the subtraction
operator. It is used to subtract the second value from the
first value.
Example :
SUBTRACTION OPERATORS

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3. Multiplication Operator : In Python, * is the
multiplication operator. It is used to find the product of 2
values.
Example :
MULTIPLICATION OPERATORS

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4. Division Operator : In Python, / is the division operator.
It is used to find the quotient when first operand is divided
by the second.
Example :
DIVISION OPERATOR

30. 30
• 5. Modulus Operator : In Python, % is the modulus
operator. It is used to find the remainder when first
operand is divided by the second.
Example :
MODULUS OPERATOR

31. 31
6.Exponentiation Operator : In Python, ** is the
exponentiation operator. It is used to raise the first
operand to power of second.
Example :
EXPONENTIATION OPERATOR

32. 32
• 7. Floor division : In Python, // is used to conduct the
floor division. It is used to find the floor of the quotient
when first operand is divided by the second.
Example :
FLOOR DIVISION

33. LOGICAL OPERATOR
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• Logical Operators in Python are used to perform logical
operations on the values of variables.
• The value is either true or false. We can figure out the conditions
by the result of the truth values.
• There are mainly three types of logical operators in
python : logical AND, logical OR and logical NOT.

34. 34
Operator Description Example
and Returns True if both
statements are true
x < 5 and x < 10
or Returns True if one of
the statements is true
x < 5 or x < 4
not Reverse the result,
returns False if the result
is true
not(x < 5 and x <
10)
TYPES OF LOGICAL OPERATORS

35. CONDITIONAL STATEMENT
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Conditional statements are also called decision-making statements.
We use those statements while we want to execute a block of code
when the given condition is true or false.
Type of condition statement in Python:
If statement.
If Else statement.
Elif statement.
Nested condition

36. 36
Syntax is:
if(condition):

37. IF STATEMENT
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• If statement is most usually used as a conditional statement.

38. IF ELSE STATEMENT IN PYTHON
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• The if…else statement in Python is used
for decision making.
• The block of lines indented the same amount after
the colon (:) will be executed whenever the
condition is TRUE.

39. 39
• If-else program:
PROGRAMS FOR IF-ELSE

40. ELIF STATEMENT
40
• Elif is a shortcut of else if condition statements. In Python
one or more conditions are used in the elif statement
For Example :

41. 41
• Nested if statements means an if statement inside
another if statement.
• When a program selects one of many paths, it can use nested or
chained conditions.
For Example:
NESTED CONDITION

42. 42
• A loop is used for iterating over a sequence (that is either a list, a
tuple, a dictionary, a set, or a string).
• With the for loop we can execute a set of statements, once for each
item in a list, tuple, set etc.
For Example:
LOOPS IN PYTHON

43. INTRO​ TO FOR LOOPS IN PYTHON​
43
• A for loop is used for iterating over a sequence (that is
either a list, a tuple, a dictionary, a set, or a string).
• With the for loop we can execute a set of statements,
once for each item in a list, tuple, set etc.
For Example:

44. PROGRAMS FOR LOOPS
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• Loop program:
• While loop program:

45. 45
• With the while loop we can execute a set of statements
as long as a condition is true.
For Example:
WHILE LOOP IN PYTHON

46. Basic Concepts of Object-Oriented
Programming In Python
46
• Object-Oriented Programming(OOP), is all about creating “objects”.
• The concept of OOP in Python focuses on creating reusable code.
• Major Python OOPs concept-
• Class.
• Object.
• Inheritance.
• Encapsulation.

47. Class
47
• A class is a blueprint for the object.
• It is a logical entity that has some specific attributes and
methods.
• The example for class of parrot can be :
class Parrot:
pass
• The class keyword is use to define an empty class Parrot.
• From class, we construct instances. An instance is a
specific object created from a particular class.

48. Object
48
• The object is an entity that has state and behavior.
• The object is an entity that has state and behavior.
• When we define a class, it needs to create an object to
allocate the memory.
Class Definition Syntax: class ClassName: # Statement-1 . . . # Statement-N
• Class Definition Syntax:
class ClassName:
# Statement-1
……
# Statement-N

49. ENCAPSULATION
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• we can restrict access to methods and variables that prevents
data from direct modification which is called encapsulation.
• In encapsulation code and data are wrapped together within a
single unit .
• Encapsulation prevents your code from unauthorized user’s.
• For example:
Class Definition Syntax: class ClassName: # Statement-1 . . . # Statement-N

50. INHERITANCE
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• Inheritance is the most important aspect of object-oriented
programming, which simulates the real-world concept of inheritance.
• It specifies that the child object acquires all the properties and
behaviors of the parent object.
• By using inheritance, we can create a class which uses all the
properties and behavior of another class.

51. TYPES OF INHERITANCE
51

52. FUNCTIONS
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• A function is a block of code which only runs when it is called.
• The idea is to put some commonly or repeatedly done task together
and make a function so that instead of writing the same code again
and again for different inputs, we can call the function to reuse code
contained in it over and over again.

53. 53
USES OF LENGTH FUNCTION
Length : len() function is an inbuilt function in Python
programming language that returns the length of the string.
Syntax:
len(string)
For Example:

54. 54
• The filter() method constructs an iterator from elements of an
iterable for which a function returns true.
• Python's filter() is a built-in function.
• The filter function takes in two arguments
SYNTAX:
filter(function, iterable)
PROGRAM ON FILTER FUNCTION

55. UNDERSTANDING LAMBDA FUNCTIONS
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• A lambda function is a small, anonymous function
that take any number of arguments but only have one
expression.
• We create them with the lambda keyword instead of the
traditional def keyword.

56. OVERVIEW OF MAP FUNCTIONS
56
• Map is a function that takes as an input a collection
Example:
• a list [‘BBA’,’MBA’,’BCA’], and a function e.g. upper().
• Then it will move every element of the collection through this function
and produce a new collection with the same count of elements.
SYNTAX:
map(function, iterables)

57. 57
• The reduce() function, as the name describes, applies a given
function to the iterables and returns a single value.
• The reduce() function is defined in the functools module.
• The reduce function can take in three arguments, two of which are
required.
reduce(function, iterable [, initializer])
SYNTAX:
reduce(function, iterables)
PROGRAM ON REDUCE FUNCTION

58. EXPLORING COMMONLY USED BUILT IN
FUNCTIONS
58
• The min() function returns the item with the lowest value, or the
item with the lowest value in an iterable.
For Example:

59. 59
The max() function returns the item with the highest
value, or the item with
MAX FUNCTION IN PYTHON

60. 60
• The sort() method sorts the list ascending by default.
For Example:
SORT FUNCTION IN PYTHON

61. PROGRAMS USING USER DEFINED FUNCTIONS
61
• A user-defined function (UDF) is a function provided by the user of
a program or environment.
For Example:
Here sum is the user define function.

62. Methods
62
• A method in python is somewhat similar to a function, except it is
associated with object/classes.
• Method is called by its name, but it is associated to an
object (dependent).
• A method is implicitly passed the object on which it is invoked.

63. 63
• For example:
PROGRAM SHOWING THE USE OF METHODS

64. ARGUMENT’S
64
• An argument is the value that are sent to the function when it is
called.
• Types of Arguments in Python Function Definition:
1.Default arguments :default arguments are values that are
provided while defining functions.
2.Keyword arguments: Functions can also be called using keyword
arguments , But all the keyword arguments should match the
parameters in the function definition.
3.Positional arguments: During function call, values passed
through arguments should be in the order of parameters in the
function definition. This is called positional arguments.

65. WORKING WITH FUNCTIONS WITH AND WITHOUT ARGUMENTS
65
Program without arguments:

66. 66
PROGRAM WITH ARGUMENTS:

67. LOGIC FLOWCHARTS
(Intuitive understanding of code flow)
67
• A flowchart typically shows the flow of data in a process,
• It provides a pictorial representation of the algorithm
detailing the steps more clearly , thus flow charts are easily
understandable.

68. DIAGRAMATICAL REPRESENTATION OF A FLOW
CHART
68

69. PSEUDOCODE
69
• Pseudocode is a method of planning which enables the
programmer to plan without considering about the
syntax.
• It has no syntax like any of the programming language
and thus can’t be compiled or interpreted by the
computer.

70. LIST COMPREHENSION​
70
• List comprehension offers a shorter syntax when you want
to create a new list based on the values of an existing list.
For Example:

71. USE CASES VS LOOPS
71
• A use case is a methodology used in system analysis to identify,
clarify and organize system requirements.
• It also defines a list of steps that illustrate how a process will be
carried out in a system.
• While Loops in Python is used to iterate over a sequence
(list, tuple, string) or other iterable objects.
• Iterating over a sequence is called traversal.

72. PRACTICE LIST COMPREHENSIONS
72
• List Comprehensions is a very powerful tool, which creates a new list
based on another list, in a single, readable line.

73. FUNCTIONS WITH RETURN ITEMS
73
• A return statement is used to end the execution of the function call
and “returns” the result (value of the expression following the
return keyword) to the caller.
The statements after the return statements are not executed.
Syntax:
def fun():
statements
return [expression]

74. Thank You !!!
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