Python Lists Lecture Notes

Introduction to Lists

• Python lists are similar to arrays in languages like C, C++, and Java.
• Can hold different types of data (numbers, strings, etc.) in a single list.

Creating Lists

• To create a list, use square brackets [ ] and separate values with commas.

  nums = [25, 12, 636, 95, 14]
  

• Can print the entire list with print(nums).

Accessing List Elements

• Access elements using index values (0-based indexing).
• Example: nums[0] returns the first element (25).
• Can also access the last element using negative indexing: nums[-1] returns 14.

Slicing Lists

• Slicing allows retrieval of a range of elements.
  • Example: nums[2:] retrieves third element to the end.
• Similar to string slicing used previously.
• Can use negative indexing for slicing as well.

Lists with Different Data Types

• Lists can contain mixed data types:

  values = [9.5, 'name', 25]
  

Nested Lists

• Lists can contain other lists (nested lists).

  mil = [nums, names]
  

List Methods and Mutability

• Lists are mutable (can be changed after creation).
• Common list methods:
  • append(value): Adds a value at the end.
  • insert(index, value): Inserts a value at a specific index.
  • remove(value): Removes the first occurrence of the specified value.
  • pop(index): Removes and returns the item at the specified index (or last item if no index is provided).
  • clear(): Removes all items from the list.
  • extend([other_values]): Adds multiple elements to the end of the list.

Examples of List Operations

• Appending values:

  nums.append(45)
  

• Inserting values:

  nums.insert(2, 2077)
  

• Removing values:

  nums.remove(14)
  

• Using pop:

  nums.pop(1)
  

• Using del to remove a range of elements:

  del nums[2:]  # Deletes from index 2 to end
  

Using Python Built-in Functions

• List has built-in functions to find min, max, sum:
  • min(nums) - returns minimum value.
  • max(nums) - returns maximum value.
  • sum(nums) - returns total sum.
  • sort() - sorts the list in ascending order.

Conclusion

• Lists offer a versatile way to store collections of data in Python.
• Ability to hold multiple data types, perform operations, and modify content dynamically.
• Encourage viewers to explore the documentation for more methods and features.

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