Datatypes in python

In Python, data types define the type of a value or a variable. Python is dynamically typed, meaning you don’t need to declare the type of a variable when you create it. The interpreter infers the type based on the value assigned.

Here are the primary data types in Python:

1. Numeric Types

• int (Integer): Represents whole numbers without a decimal point.

  x = 10
  y = -5
  z = 0

• float (Floating-point number): Represents real numbers or numbers with a decimal point.

  pi = 3.14
  temperature = -2.5

• complex (Complex number): Represents numbers with a real and imaginary part.

  a = 2 + 3j  # real part is 2, imaginary part is 3
  b = 1 - 4j

2. Text Type

• str (String): Represents sequences of characters (text). Strings can be enclosed in single quotes (') or double quotes (").

  greeting = "Hello, World!"
  name = 'Alice'

3. Sequence Types

• list: An ordered, mutable collection of elements. Lists are enclosed in square brackets ([]), and elements can be of any type.

  fruits = ['apple', 'banana', 'cherry']
  numbers = [1, 2, 3, 4]
  mixed_list = [1, "apple", 3.14]

• tuple: An ordered, immutable collection of elements. Tuples are similar to lists, but once created, you cannot modify them. Tuples are enclosed in parentheses (()).

  coordinates = (10, 20)
  colors = ('red', 'green', 'blue')

• range: A special type of sequence used for generating a sequence of numbers, commonly used in loops.

  numbers = range(5)  # 0, 1, 2, 3, 4

4. Mapping Type

• dict (Dictionary): An unordered collection of key-value pairs. Dictionaries are enclosed in curly braces ({}), with keys and values separated by a colon (:).

  person = {"name": "Alice", "age": 25, "city": "New York"}

5. Set Types

• set: An unordered collection of unique elements. Sets are enclosed in curly braces ({}) or can be created using the set() function. They do not allow duplicates.

  unique_numbers = {1, 2, 3, 4}
  letters = set("apple")

• frozenset: Similar to sets, but immutable. Once created, you cannot modify the elements in a frozenset.

  frozen_set = frozenset([1, 2, 3, 4])

6. Boolean Type

• bool: Represents one of two values: True or False. It is used for conditional statements and logical operations.

  is_active = True
  is_sunny = False

7. Binary Types

• bytes: Immutable sequences of bytes, often used for binary data and file handling.

  byte_data = b'hello'

• bytearray: A mutable version of bytes. It allows modification of byte sequences.

  byte_array = bytearray([65, 66, 67])

• memoryview: A view object that allows you to access and manipulate the underlying data of byte arrays without copying the data.

  mem_view = memoryview(byte_array)

8. None Type

• None: A special type representing the absence of a value or a null value.

  result = None

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Example Usage of Data Types:

# Integer
age = 30

# Float
height = 5.9

# String
name = "Alice"

# List
colors = ["red", "green", "blue"]

# Tuple
coordinates = (10, 20)

# Dictionary
person = {"name": "Alice", "age": 30, "city": "New York"}

# Set
fruits = {"apple", "banana", "cherry"}

# Boolean
is_sunny = True

# None
status = None

# Complex number
number = 3 + 4j

Type Conversion (Casting):

You can convert between different data types in Python using functions like int(), float(), str(), etc.

# Convert float to integer
x = 3.14
y = int(x)  # y = 3

# Convert string to integer
s = "100"
n = int(s)  # n = 100

Type Checking:

You can check the type of a variable using the type() function.

x = 10
print(type(x))  # Output: <class 'int'>

y = "Hello"
print(type(y))  # Output: <class 'str'>

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Understanding these basic data types is essential for writing efficient and readable Python code.