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Python Data Types

Written by Rahul Lath

Updated on: 07 Dec 2023

Python Tutorials

1Python Overview2Python Tutorial: A Comprehensive Guide for Beginners3Python Keywords and Identifiers4Download and Installation Guide for Python5Python Syntax (With Examples)6Python Comments7Python Variables (With Examples)8Taking Input in Python9Output in Python10File Handling in Python (Files I/O)11Python Operators (With Examples)12Ternary Operators in Python13Operator Overloading in Python14Division Operators in Python15Input from Console in Python16Output Formatting in Python17Any All in Python18Difference between Python Equality and Identity Operators19Python Membership and Identity Operators20Python Data Types21Python Dictionary22Control Flow in Python23Python Arrays24Looping Techniques in Python25Chaining Comparison Operators in Python26Python Functions27Python Strings28Python Numbers29Python Sets30Python For Loops31Python While Loops32Python Break Statement:33Python Continue Statement34Python pass Statement35Args and Kwargs in Python36Python Generators37Python Lambda38Global and Local Variables in Python39Global Keyword in Python40Python Closures41Python Decorators42Memoization using Decorators in Python43Constructors in Python44Encapsulation in Python45Inheritance in Python46Polymorphism in Python47Class Method vs Static Method in Python48Python Exception Handling49First Class Functions in Python50Python Classes And Objects51Errors and Exceptions in Python52Built-In Exceptions in Python53Append to file in Python54File Handling in Python55Destructors in Python56User-Defined Exceptions in Python57Class or Static Variable in Python58Python Tuples59Reading File in Python60Writing File in Python61Opening and Closing Files in Python62NZEC error in Python63Operator Function64Webscraper Python Beautifulsoup65Python Pyramid Patterns66Python Start Patterns67Web Crawler in Python68Build a Python Youtube Downloader69Currency Convertor in Python70Python Website Blocker
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What are Python Data Types?

We need to use data in order to make our programs function. Data is the term used in computer science to describe the information that a computer processes. The various categories of data that are used in python to represent a wide range of values are known as python data types. A program’s functionality can be significantly impacted by the type of data we use in it. Therefore, understanding python data types is crucial for programming.

There are many different data types in the widely used programming language Python. These data types are used to represent various types of data, including dates, text, and numbers. In this article, we will discuss the different data types in Python and how they are used.

Numeric Data Types

In Python, numbers are represented by numeric data types. There are three main numeric Python data types:

  1. Integer (int): Integers are whole numbers, meaning they do not have any decimal places. Integers can be positive or negative, and they have no upper limit to their value.

Examples of how to use int in code:

x = 10 y = -5 z = 0

Common operations and functions used with int:

  • Addition: x + y
  • Subtraction: x – y
  • Multiplication: x * y
  • Division: x / y
  • Modulus: x % y
  • Power: x ** 2
  1. Float (float): Floats are used to represent numbers that have decimal places. They can be positive or negative, and they have a limited range of values.

Examples of how to use float in code:

x = 3.14 y = -2.5 z = 0.0

Common operations and functions used with float:

  • Addition: x + y
  • Subtraction: x – y
  • Multiplication: x * y
  • Division: x / y
  • Modulus: x % y
  • Power: x ** 2
  1. Complex (complex): Complex numbers are used to represent numbers that have both a real and imaginary part. They are expressed in the form of a + bj, where a is the real part and b is the imaginary part.

Examples of how to use complex in code:

x = 3 + 4j y = 2 - 5j z = 0j

Common operations and functions used with complex:

  • Addition: x + y
  • Subtraction: x – y
  • Multiplication: x * y
  • Division: x / y

String Data Type

In Python, a series of characters are represented by the string data type. Single or double quotes are used to enclose strings. They may contain any alphabetical, numeric, or symbolic combination.

Examples of how to create and manipulate strings in code:

# Creating a string message = "Hello, World!" # Accessing characters in a string print(message[0]) # Output: H print(message[-1]) # Output: ! # Slicing a string print(message[0:5]) # Output: Hello print(message[7:]) # Output: World! # Concatenating strings first_name = "John" last_name = "Doe" full_name = first_name + " " + last_name print(full_name) # Output: John Doe # Converting case print(message.upper()) # Output: HELLO, WORLD! print(message.lower()) # Output: hello, world! # Replacing characters new_message = message.replace("World", "Python Data Types") print(new_message) # Output: Hello, Python Data Types!

Common string operations and functions:

  • Length: len()
  • Concatenation: +
  • Slicing: []
  • Replace: replace()
  • Upper and lower case: upper(), lower()
  • Strip whitespace: strip()

Boolean Data Type

The boolean data type in Python is used to represent truth values. It can have only two values: True and False. Boolean values are often used in programming to make decisions based on whether a condition is true or false.

Examples of how to use boolean values in code:

x = 10 y = 5 # Comparing values print(x > y) # Output: True print(x == y) # Output: False print(x != y) # Output: True # Logical operators print(x > y and x != y) # Output: True print(x < y or x == y) # Output: False # Assigning boolean values is_raining = True is_sunny = False

Common boolean operations and functions:

  • Comparison operators: >, <, ==, !=, >=, <=
  • Logical operators: and, or, not
  • Converting values to boolean: bool()

Sequence Data Types

In Python, collections of values are represented by sequence data types. Lists, tuples, and range are the three primary sequence data types in Python.

Explanation of sequence data types in Python:

  1. Lists: Lists are used to represent an ordered collection of values. Lists are mutable, which means that we can add, remove, or modify items in the list.
  2. Tuples: Tuples are used to represent an ordered collection of values. Tuples are immutable, which means that once we create a tuple, we cannot add, remove, or modify items in the tuple.
  3. Range: Range is used to represent a sequence of numbers. It is often used in loops to iterate over a specific range of values.

Examples of how to create and manipulate each sequence data type in code:

# Creating a list fruits = ["apple", "banana", "cherry"] # Accessing items in a list print(fruits[0]) # Output: apple print(fruits[-1]) # Output: cherry
# Modifying items in a list fruits[1] = "orange" print(fruits) # Output: ['apple', 'orange', 'cherry'] # Creating a tuple months = ("January", "February", "March")
# Accessing items in a tuple print(months[0]) # Output: January print(months[-1]) # Output: March # Creating a range numbers = range(0, 10) # Iterating over a range for number in numbers: print(number) # Output: 0 1 2 3 4 5 6 7 8 9

Common sequence operations and functions:

  • Length: len()
  • Concatenation: +
  • Repetition: *
  • Slicing: []
  • Modifying: append(), insert(), remove(), pop()
  • Converting to other sequence types: list(), tuple()

Set and Dictionary Data Types

Python uses the set and dictionary data types to represent collections of values that aren’t necessarily in any particular order.

Explanation of the set and dictionary data types in Python

  1. Set: Sets are used to represent an unordered collection of unique values. Sets are mutable, which means that we can add, remove, or modify items in the set.
  2. Dictionary: Dictionaries are used to represent a collection of key-value pairs. Each key is associated with a value, and we can use the key to access the corresponding value. Dictionaries are mutable, which means that we can add, remove, or modify key-value pairs in the dictionary.

Examples of how to create and manipulate sets and dictionaries in code:

# Creating a set fruits = {"apple", "banana", "cherry"} # Adding items to a set fruits.add("orange") print(fruits) # Output: {'cherry', 'apple', 'banana', 'orange'}
# Removing items from a set fruits.remove("banana") print(fruits) # Output: {'cherry', 'apple', 'orange'} # Creating a dictionary person = { "name": "John", "age": 30, "city": "New York" }

# Accessing items in a dictionary print(person[&#8220;name&#8221;]) # Output: John print(person.get(&#8220;age&#8221;)) # Output: 30

&nbsp; # Modifying items in a dictionary person[&#8220;age&#8221;] = 40 print(person) # Output: {&#8216;name&#8217;: &#8216;John&#8217;, &#8216;age&#8217;: 40, &#8216;city&#8217;: &#8216;

Type Conversion in Python

In Python, type conversion refers to the transformation of one data type into another. Python comes with built-in functions for converting data between different data types. 

Explanation of type conversion in Python:

  1.  Implicit Type Conversion: Python automatically converts one data type to another when necessary using implicit type conversion. For instance, Python will convert the integer to a float before performing the addition if we attempt to add an integer and a float. 
  2. Explicit Type Conversion: By using built-in functions, we can also explicitly convert data from one type to another. For instance, we can convert an integer to a string using the str() function.

Examples of how to convert data types in code:

# Implicit Type Conversion x = 10 # int y = 3.14 # float z = x + y print(z) # Output: 13.14
# Explicit Type Conversion a = "10" # string b = int(a) print(b) # Output: 10 c = "3.14" # string d = float(c) print(d) # Output: 3.14

Common type conversion functions:

  • int(): Converts to an integer
  • float(): Converts to a float
  • str(): Converts to a string
  • bool(): Converts to a boolean
  • list(): Converts to a list
  • tuple(): Converts to a tuple
  • set(): Converts to a set
  • dict(): Converts to a dictionary


The various Python data types and their applications were covered in this article. We discussed a variety of data types, including boolean, string, boolean, sequence (lists, tuples, and range), set, and dictionary data types. We also talked about data type conversion and how to change one type of data into another.

Programming requires a thorough understanding of data types because doing so can increase code productivity and reduce bugs. We can make sure that our code is clear to understand and maintain by using the right data type for each value in our program. 


What are Python’s four different data types?

There are more than 4 python data types , but the four main built-in data types are integer, float, string, and boolean.

What are the 5 data types in Python?

The five main built-in python data types are integer, float, string, boolean, and complex.

What is a datatype in Python?

A data type in Python is a category of values that defines the operations that can be performed on those values.

How many data types are in Python?

Python has many built-in data types, including numeric types (int, float, complex), string, boolean, sequence types (list, tuple, range), and set and dictionary types.

Written by

Rahul Lath

Reviewed by

Arpit Rankwar

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