Python Data Types

Python 3 offers a rich set of data types that are used to store various kinds of data. Here’s an overview of the fundamental data types in Python 3:

1. Numeric Types

1. int (Integer)
   • Represents whole numbers, positive or negative, without a fractional component.
   • Example: 5, -42, 0
2. float (Floating-Point Number)
   • Represents real numbers with a fractional component, stored as a decimal point.
   • Example: 3.14, -0.001, 2.0
3. complex
   • Represents complex numbers, which are numbers with a real and imaginary part.
   • Example: 3 + 5j, where 3 is the real part and 5j is the imaginary part.

2. Sequence Types

1. str (String)
   • Represents a sequence of characters (text). Strings are immutable, meaning they cannot be changed after they are created.
   • Example: "Hello, World!", 'Python 3'
2. list
   • Represents an ordered collection of items, which can be of different data types. Lists are mutable, meaning their content can be changed.
   • Example: [1, 2, 3], ["apple", "banana", "cherry"]
3. tuple
   • Similar to a list, but tuples are immutable. Once a tuple is created, its content cannot be modified.
   • Example: (1, 2, 3), ("apple", "banana", "cherry")
4. range
   • Represents an immutable sequence of numbers, typically used for looping a specific number of times.
   • Example: range(5) generates the numbers 0, 1, 2, 3, 4.

3. Set Types

1. set
   • Represents an unordered collection of unique items. Sets are mutable.
   • Example: {1, 2, 3}, {"apple", "banana", "cherry"}
2. frozenset
   • Represents an immutable version of a set. Once created, the items in a frozenset cannot be modified.
   • Example: frozenset([1, 2, 3]), frozenset({"apple", "banana", "cherry"})

4. Mapping Types

1. dict (Dictionary)
   • Represents a collection of key-value pairs, where each key is unique. Dictionaries are mutable.
   • Example: {"name": "Alice", "age": 25}, {1: "one", 2: "two", 3: "three"}

5. Boolean Type

1. bool
   • Represents a logical value, either True or False.
   • Example: True, False

6. Binary Types

1. bytes
   • Represents an immutable sequence of bytes (8-bit values).
   • Example: b"Hello, World!"
2. bytearray
   • Represents a mutable sequence of bytes.
   • Example: bytearray(b"Hello, World!")
3. memoryview
   • Provides a view of another binary sequence, such as bytes or bytearray, without copying the data.
   • Example: memoryview(b"Hello, World!")

7. None Type

1. NoneType
   • Represents the absence of a value or a null value. There is only one value of this type, which is None.
   • Example: None

8. User-Defined Types

1. Classes: In Python, you can define your own data types using classes. These custom types can be as simple or complex as needed for your application.

Type Checking and Conversion

1. Type Checking: You can check the type of a variable using the type() function.
   • Example: type(5) returns <class 'int'>.
2. Type Conversion: Python provides functions to convert between data types.
   • Example: int("123") converts a string to an integer, str(123) converts an integer to a string.

These are the fundamental data types in Python 3. Understanding them is crucial for writing efficient and effective Python code.