What are the different types of Collections in Python. Give each one of them its defininition and its example.

In Python, there are several types of collections that can be used to store and organize data. Here are the different types of collections along with their definitions and examples:

1. Lists: Lists are ordered collections that can store elements of different data types. They are mutable, meaning that you can modify the elements in a list. Lists are defined using square brackets [] and elements are separated by commas. For example: my_list = [1, 2, "hello", True]

2. Tuples: Tuples are similar to lists, but they are immutable, meaning that you cannot modify the elements once they are assigned. Tuples are defined using parentheses () and elements are separated by commas. For example: my_tuple = (1, 2, "hello", True)

3. Sets: Sets are unordered collections that store unique elements. They do not allow duplicate values. Sets are defined using curly braces {} or the set() function. For example: my_set = {1, 2, 3, 4} or my_set = set([1, 2, 3, 4])

4. Dictionaries: Dictionaries are unordered collections that store key-value pairs. Each element in a dictionary is accessed by its key rather than its index. Dictionaries are defined using curly braces {} and key-value pairs are separated by colons :. For example: my_dict = {"name": "John", "age": 25, "city": "New York"}

5. Arrays: Arrays are collections that can store elements of the same data type. They are similar to lists but are more efficient for numerical computations. Arrays are defined using the array module in Python. For example: import array my_array = array.array('i', [1, 2, 3, 4])

These are the different types of collections in Python along with their definitions and examples.