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Python Data Types

An overview of some commonly used data types in Python:

  1. Integers (int): Integers are whole numbers without any decimal point. For example: -1, 0, 42.
  2. Floats (float): Floats represent real numbers with a decimal point or in exponential form. For example: 3.14, 2.71828, 1.0e-5.
  3. Strings (str): Strings are sequences of characters, enclosed in single, double, or triple quotes. For example: 'hello', "world", '''multiple lines'''.
  4. Lists (list): Lists are ordered collections of items that can be of any data type, including other lists. They are mutable, meaning you can change the elements in a list. For example: [1, 2, 3], ['apple', 'banana', 'mango'].
  5. Tuples (tuple): Tuples are similar to lists, but they are immutable, meaning you can’t change their elements after they’re defined. For example: (1, 2, 3).
  6. Dictionaries (dict): Dictionaries are collections of key-value pairs. They allow you to access values by their associated keys. For example: {'name': 'Shyam', 'age': 30}.
  7. Sets (set): Sets are unordered collections of unique items. They are useful for tasks like removing duplicates from a list. For example: {1, 2, 3}.
  8. Booleans (bool): Booleans represent truth values, either True or False.
  9. NoneType (None): This is a special data type that represents the absence of a value.
  10. Bytes and Byte Arrays (bytes, bytearray): These are used to represent sequences of bytes.
  11. Complex Numbers (complex): These are used to represent complex numbers with a real and an imaginary part.
  12. Ranges (range): This is used to represent a sequence of numbers.
  13. File Objects (file): These represent opened files in your computer.

These are the fundamental data types in Python, and they can be used to build more complex data structures and perform various operations. Keep in mind that Python is dynamically typed, which means you don’t have to explicitly declare the data type of a variable. The interpreter infers it based on the value assigned to it.