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What is Python ? Statement , Operators and Data Type in Python

What is Python?

Python is a powerful, general-purpose, high-level programming language created by Guido van Rossum and first released in 1991.

Common Uses of Python:

  • Web Development: Python frameworks like Django and Flask are popular for building web applications.
  • Data Science and Machine Learning: Python libraries like NumPy, Pandas, TensorFlow, and sci-kit-learn make it a powerful tool for data analysis and machine learning tasks.
  • Automation: Python scripts can be used to automate repetitive tasks on your computer.
  • Scripting: Python is often used for scripting various tasks, such as system administration, network automation, and testing.
  • Scientific Computing: Python is used in scientific computing due to its numerical computing libraries like NumPy and SciPy.

  • Python is Simple and easy.
  • Python is Free and Open Source.
  • Python High-level language.
  • Python is portable.
  • Python was developed by Guido Van Rossum.

What is Python ? Statement , Operators and Data Type in Python

Why to Use Python?

Here are some of the compelling reasons why Python is a popular and widely used programming language.

  •  Programming (for Placements/online contests/DSA)
  • Development (using a backend framework called Django)
  • Machine Learning / Data Science / Artificial Intelligence

What to Install IDE?

Choosing the right Integrated Development Environment (IDE) depends on your specific needs and preferences. Here's a breakdown of some popular options to help you decide.


Python Character Sets-

character sets aren't explicitly defined as data structures you work with directly. However, Python internally handles characters using a character encoding, which specifies how characters are represented as binary data. The most common character encoding used in Python is Unicode (UTF-8 by default).


  • Letters – A to Z, a to z Digits – 0 to 9.
  • Special Symbols - + - * / etc.
  • Whitespaces – Blank Space, tab, carriage return, newline, formfeed.
  • Other characters – Python can process all ASCII and Unicode characters as part of data or literals.
  • Variables in Python-
  • Variables Basic Types in Python- numbers(integers, floating), boolean, strings.


Python Data Types --

Data types are fundamental in Python programming. They define the type of value a variable can hold and the operations that can be performed on that data. Here's a breakdown of the core data types in Python.


  • String()
  • Integers()
  • Float()
  • Boolean()
  • complex()
  • None()


  • int(): Represents integers (whole numbers) like 42 or -100.
  • float(): Represents floating-point numbers (decimals) like 3.14 or -9.25e+2 (scientific notation).
  • complex(): Represents complex numbers with a real and imaginary part (a+bi), where i is the imaginary unit.
  • ()str: Represents strings of text enclosed in single or double quotes. Example: "Hello world!" or 'This is a string'
  • ()bool: Represents Boolean values, True or False.

Data Types --


  • print(type(name))  ----- <class 'str'>
  • print(type(age))  ------ <class 'int'>
  • print(type(pi))  ----- <class 'float'>
  • print(type(A)) -----  <class 'boolean'>
  • Print(type(complex_num)) -----   <class 'complex'>


Python Keywords-

 Keywords are reserved words in Python keywords are special words with reserved meanings. These keywords define the syntax and structure of the language and cannot be used as variable name or function names.

Here's a categorization of some important Python keywords:








































Comments in Python-

Comments in Python are essential elements that enhance code readability and maintainability. They are instructions or explanations meant for humans, not the Python interpreter itself. Here's a breakdown of comments in Python.


1-Single-Line Comments:

  • These start with the hash symbol (#) and extend to the end of the line.
  • They are useful for brief explanations or comments next to code lines.


#single line comments

2-Multi-Line Comments:

  • Python doesn't have a dedicated syntax for multi-line comments like some other languages.
  • There are two common approaches to achieving multi-line comments.


""" multi-line comment """

Operators in Python -

An operator is a symbol that performs a certain operation between operands. Operators in Python are the workhorses of your programs. They perform operations on variables and values, allowing you to manipulate data, perform calculations, compare values, and control the flow of your code.


  • Arithmetic Operators - ( +, -, *, /, **, / .


  • Relational / Comparison Operators- (==, !=, >, <, >, <= )
  • Assignment Operators - (=, +, -, *, /,%, **)
  • Logical Operators - (not, and, or)


Type Conversion in Python-

Python, type conversion, also known as typecasting, refers to the process of transforming a value from one data type to another.


  • str()
  • int()
  • bool()
  • float()


Correct -

a,b = 1,2




a,b = 1, "2"
c= a+b

Type Casting in Python-

In Python, type casting, also known as type conversion, is the process of transforming a value from one data type to another. It's essentially a way to tell Python to interpret the data in a specific way.


  • int(y [base]) - It converts y to an integer, and Base specifies the number base. For example, if you want to convert the string in decimal numbers then you'll use 10 as base.
  • float(y) - It converts y to a floating-point number..
  • complex(real [imag]) - It creates a complex number.
  • str(y) - It converts y to a string.
  • tuple(y) - It converts y to a tuple.
  • list(y) - It converts y to a list.
  • set(y) - It converts y to a set.
  • dict(y)It creates a dictionary and y should be a sequence of (key, value) tuples.
  • ord(y) - It converts a character into an integer.
  • hex(y) - It converts an integer to a hexadecimal string.
  • oct(y) - It converts an integer to an octal string


Type Costing -

When working with data types in Python, there are performance considerations to keep in mind. Different data types have varying memory usage and processing speeds.


a,b = 2, "5"
c =int(b)
sum= a+b

Output- 7


a, b = "2" , "5"
c = int(2) + int(5)

Output- 7


Input in Python -

The input() function. This function pauses your program's execution and waits for the user to enter some data. Here's a breakdown of how it works:

  • input( ) statement is used to accept values (using the keyboard) from the user.
  • input() - result for input() always in str. ( "Rahulwebtech")
  • int(input()) - int value  (1, 2, 3, 4, 5)
  • float(input()) - float value (1.0, 2.0, 3.2, 4.3)


String Example -


name=input("My Name Is Rahul Bharadwaj?")


print(" Thanks ....")


The string is a data type that stores a sequence of characters. 

Basic Operations 


concatenation “hello” + “world” ------>hello word

length of str 


Indexing in Python-

Indexing in Python is a fundamental concept used to access specific elements within sequences like strings, lists, and tuples. It relies on numerical positions assigned to each element within the sequence.

str = "Rahul_Bharadwaj"

str[0] is "R" str[1] is "a"

Slicing in Python -  

Slicing in Python is a powerful technique for extracting subsets of elements from sequences like strings, lists, and tuples. It allows you to create new sequences based on specific criteria without modifying the original sequence itself.

Syntex -

str[ starting index : Ending index]

str = "Rahul_Bharadwaj"

str[ 2 : 4 ] is "hul"

str[ : 4] is same str[ 0 : 4]

str[ 2 :  ] is same str[ 2 : len(str)]

String Functions in Python-

Strings are fundamental data types in Python used to represent textual data. Python provides a rich set of built-in functions and methods for working with strings.

  • str = “I am a coder.” 
  • str.ends with(“er.“)  - returns true if string ends with substrate 
  • str.capitalize( )  - capitalizes 1st char 
  • str. replace( old, new )  - replaces all occurrences of old with new 
  • str.find( word )  - returns 1st index of 1st occurrence Apna College 
  • str.count(“am“)  - counts the occurrence of substr in string

Conditional Statements -

Conditional statements are fundamental building blocks in any programming language. They allow your program to make decisions based on certain conditions, leading to different execution paths.

if-elif-else (SYNTAX) 

if(condition) : 




else: StatementN

Conditional Statements Example-

Grade students based on marks 

marks >= 90, grade = “A” 

90 > marks >= 80, grade = “B” 

80 > marks >= 70, grade = “C” 

70 > marks, grade = “D”

Lists in Python

 A built-in data type that stores a set of values It can store elements of different types (integer, float, string, etc.) Lists are one of the most fundamental and versatile data structures in Python. They are used to store collections of items in a specific order and allow you to access, modify, and iterate through these elements.

marks = [86, 62, 73, 65, 86]

student = [”Rahul”, 68, “Delhi”]

student[0] = “Arya” 


List Slicing in Python-Similar to String Slicing. 

 list_name[ starting_idx : ending_idx ] - ending idx is not included 

marks = [87, 64, 33, 95, 76]

marks[ 1 : 4 ] is [64, 33, 95] 

marks[  : 4 ] - is same as marks[ 0 : 4]

 marks[ 1 :  ] - is same as marks[ 1 : len(marks) ] 

marks[ -3 : -1 ]  - is [33, 95]

List Methods in Python -

Python provides a rich set of built-in methods for working with lists. These methods allow you to add, remove, modify, search, and iterate through elements in your lists, making them more versatile and efficient.

  • list = [2, 1, 3] list.append(4)  - adds one element at the end 
  • list.sort( )  - sorts in ascending order [2, 1, 3, 4] [1, 2, 3]
  • list.sort( reverse=True )  - sorts in descending order 
  • list.reverse( )  - reverses list [3, 1, 2] [3, 2, 1]
  • list.insert( idx, el )  - insert element at index 
  • list = [2, 1, 3, 1] list.remove(1) - removes first occurrence of element 
  • list.pop( idx )  - removes element at idx [2, 3, 1]

Tuples in Python - 

A built-in data type that lets us create immutable sequences of values. Tuples in Python are ordered, immutable collections of elements, similar to lists. However, unlike lists, tuples cannot be modified after they are created.

tuple = (87, 64, 33, 95, 76) - tup[0], tup[1].. 

tuple[0] = 43 - NOT allowed in python tup1 = ( ) 

tup2 = ( 1, ) 

tup3 = ( 1, 2, 3 )

Tuple Methods in Python-

While Python tuples are immutable, meaning their elements cannot be directly modified after creation, there are still several built-in methods you can use to work with them.

tup = (2, 1, 3, 1) 

tup.index( el )  -  returns index of first occurrence 

tup.count( el )  - counts total occurrences tup.index(1) is 1 tup.count(1) is 2 

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