Python Data Types

In this tutorial, you will learn about Python Data Type.

What is Data Type in Python?

Data Types define the Type of data a variable that can hold which type of value.

Python has a lots of data types, You can see below.

1. Numeric Types

int: It represents whole numbers (positive, negative, or zero) without decimals.
Example:


x = 20
y = -10
z = 0

float: It represents numbers with decimals (floating-point numbers).


x = 20.15
y = -10.57

complex: It represents complex numbers with a real and imaginary part.

Example:


z = 5 + 10j

2. Text Type

string (str): A sequence of characters, or simply text. Strings are enclosed in quotes.

Example:


name = "John"
greeting = 'Hello Friends'

3. Sequence Types(Ordered collections)

Collections of items that follow a specific order.

list: A collection of items. You can add, remove, or change items in a list. It can hold different data types.
Example:


fruits = ["apple", "banana", "orange", 75]

Tuple: It is similar to a list, but immutable (you can’t change it after it’s created). It’s faster and safer for fixed collections.

Example:


coordinates = (10.1, 20.5, 30.5)

Range: It represents a sequence of numbers. Commonly used in loops.

Example


range(0, 10) represents numbers from 0 to 9.

4. Mapping Type

Dictionary (dict): It stores key-value pairs. You use keys (unique) to access the values.


person = {"name": "John", "age": 35}

To access the name:


person["name"] gives "John".

5. Set Types (Unordered collections)

Each item must be unique in the collection.

Set: An unordered collection of unique items (no duplicates allowed).


my_set = {1, 2, 3, "apple"}

Frozen Set: It is a immutable version of a set. it cannot be changed after created.


frozen_set = frozenset([1, 2, 3])

6. Boolean Type

Boolean (bool): It represents True or False

Example:


is_loggedin= true, is_open = false

7. Binary Types

Binary types are used to handle and manipulate binary data.

Binary Data is not a human-readable text because it’s in a byte form.

Python provides two primary binary types to represent and work with binary data:

Bytes:

1. It is an immutable sequence of bytes.

2. Each element in an bytes object is an integer and it’s rang from 0 to 255, representing an 8-bit byte.

3. It is useful for representing raw binary data, such as reading from or writing to a file in binary mode or handling binary network protocols.

4. You define bytes by prefixing a string literal with a b.


binary_data = b"hello"  # 'b' indicates this is a bytes object
print(binary_data)      # Output: b'hello'
print(binary_data[0])   # Output: 104 (ASCII value of 'h')

Bytearray:

1. It is a mutable sequence of bytes.

2. It is similar to bytes, but allows for modification of its elements.

3. Often used when you need to manipulate or modify binary data, such as changing bytes or appending new data.

4. You can create a bytearray from a bytes object or from an iterable of integers.

Example:


mutable_binary_data = bytearray(b"hello")
print(mutable_binary_data)  # Output: bytearray(b'hello')

# Modify the first byte
mutable_binary_data[0] = 72  # ASCII value of 'H'
print(mutable_binary_data)   # Output: bytearray(b'Hello')

Memoryview:

1. A memoryview object exposes the buffer interface, allowing you to work with large datasets without copying the data.

2. It is useful for slicing and modifying parts of large binary objects without creating new copies.

Example


binary_data = b"hello world"
mv = memoryview(binary_data)
print(mv[0:5])  # Output: 
print(mv.tobytes())  # Output: b'hello world'

8. None Type

None: It represents the absence of a value or a null value. It is often used as a default value or a placeholder.

Example:


result = None