Python Data Types

Python data types are classifications that define the nature of data that can be stored and manipulated within a program. These data types form the foundation for Python programming and help developers understand how the data is represented in memory and how it behaves when operated upon.

Here’s a detailed explanation of Python’s main data types with examples:

1.Numeric Data Types

These types store numeric values and allow arithmetic operations.

1.1 Integer (int)

Represents whole numbers (positive, negative, or zero).

Example:

  x = 10  # Integer
  y = -5  # Negative integer
  z = 0   # Zero
  print(type(x))  # Output: <class 'int'>

1.2. Floating-Point (float)

Represents real numbers with a decimal point.

Example:

  a = 3.14  # Float
  b = -0.75 # Negative float
  print(type(a))  # Output: <class 'float'>

1.3. Complex Numbers (complex)

Represents numbers with a real and an imaginary part.

Example:

  c = 2 + 3j  # Complex number
  print(type(c))  # Output: <class 'complex'>
  print(c.real, c.imag)  # Output: 2.0 3.0

2.Sequence Data Types

These are ordered collections of data.

2.1. String (str)

Represents sequences of characters enclosed in quotes.

Example:

  c = 2 + 3j  # Complex number
  print(type(c))  # Output: <class 'complex'>
  print(c.real, c.imag)  # Output: 2.0 3.0

2.2. List

An ordered, mutable collection of items, which can store mixed data types.

Example:

  my_list = [1, 2, 3, "Python", 3.14]
  print(type(my_list))  # Output: <class 'list'>
  my_list.append("New Element")
  print(my_list)  # Output: [1, 2, 3, 'Python', 3.14, 'New Element']

2.3. Tuple

An ordered, immutable collection of items.

Example:

  my_tuple = (1, 2, 3, "Immutable", 3.14)
  print(type(my_tuple))  # Output: <class 'tuple'>
  print(my_tuple[1])  # Output: 2

3.Mapping Data Type

Used to store data in key-value pairs.

3.1. Dictionary (dict)

A collection of key-value pairs, where keys are unique and values can be any data type.

Example:

  my_dict = {"name": "Python", "year": 1991, "version": 3.10}
  print(type(my_dict))  # Output: <class 'dict'>
  print(my_dict["name"])  # Output: Python

4.Set Data Types

These types store unordered collections of unique items.

4.1. Set

A mutable collection of unique items.

Example:

  my_set = {1, 2, 3, 3, 4}
  print(type(my_set))  # Output: <class 'set'>
  print(my_set)  # Output: {1, 2, 3, 4}

4.2. Frozen Set

An immutable version of a set.

Example:

  frozen_set = frozenset([1, 2, 3, 4])
  print(type(frozen_set))  # Output: <class 'frozenset'>

5.Boolean Type (bool)

Represents one of two values: True or False.

Example:

  is_active = True
  is_logged_in = False
  print(type(is_active))  # Output: <class 'bool'>
  print(10 > 5)  # Output: True

6.Binary Types

Used to handle binary data.

6.1. Bytes

Immutable sequences of bytes.

Example:

  byte_data = b"Hello"
  print(type(byte_data))  # Output: <class 'bytes'>

6.2. Bytearray

A mutable sequence of bytes.

Example:

  mutable_bytes = bytearray(b"Hello")
  mutable_bytes[0] = 72  # Changing the first byte
  print(mutable_bytes)  # Output: bytearray(b'Hello')

6.3. Memoryview

Provides a view of memory data without copying.

Example:

  byte_data = b"Memory"
  mv = memoryview(byte_data)
  print(mv[0])  # Output: 77 (ASCII for 'M')

7.None Type

Represents the absence of a value.

Example:

  value = None
  print(type(value))  # Output: <class 'NoneType'>

These data types allow Python to be flexible and versatile, supporting operations and applications in diverse fields such as web development, data science, and artificial intelligence.

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Python Data Types