Deleting multiple elements from a list

Fundamentals of deletion

Safely deleting elements: down-to-top

Deleting elements starting from the end of a list can help you dodge the sneaky index shifting:

my_list = ['a', 'b', 'c', 'd']
indexes_to_remove = [1, 2]  # We're trimming the fat here
# Sort in reverse order to prevent our boat from tipping
for index in sorted(indexes_to_remove, reverse=True):
    del my_list[index]  # Shiver me timbers!
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By starting from the highest index, we outsmart the index shifting phenomenon, ensuring no unintended deletions occur. It's like playing chess... with lists.

numpy: efficiency at its best

numpy enters the scene for tackling large datasets:

import numpy as np

arr = np.array(['a', 'b', 'c', 'd'])
indexes_to_remove = [1, 2]  # Indices walking the plank
arr = np.delete(arr, indexes_to_remove)
# You can avoid converting to_list for stopping numpy from going rogue
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Here, numpy's delete function offers a convenient parachute for jumping off the performance cliff faced by native Python lists when dealing with large data.

Slice it up: efficient bulk deletion

To wield the blade of efficiency in bulk deletion, embrace slice assignment:

my_list = ['a', 'b', 'c', 'd', 'e', 'f']
# Time to feast on elements from index 1 to 3
my_list[1:4] = []  # Bye Felicia!
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This bad boy slashes the elements and re-seals the list, saving the effort of concocting a new one. Fewer dishes to wash, right?

Mastering the deletion game

Condition-based deletion

When the need is to delete based on a condition, wrap an if clause within your list comprehension:

my_list = [1, 2, 3, 4, 5]
# Vanquish the even ones!
my_list = [x for x in my_list if x % 2 != 0]  # Odd ones rule!
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It's simpler to grasp than the filter() function wielding its lambda sword.

Index manipulation for dynamic deletions

For performing dynamic deletions during iteration, adjusting the index is key to avoiding chaos:

my_list = ['a', 'b', 'c', 'd', 'e']
indexes_to_remove = [0, 2, 3]

for i, index in enumerate(sorted(indexes_to_remove)):
    del my_list[index - i]  # We've got our eyes on you, deleting elements!
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This eagle-eyed approach keeps your deletions on point by accounting for the contracted indices.

List difference: a set operation

For floating the unusable elements away, consider a set operation:

my_list = set(['a', 'b', 'c', 'd'])
to_remove = set(['b', 'd'])
my_list = list(my_list - to_remove)  # It's subtraction, but for lists
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This navigation trick stays on course when you have a clear map (known elements to remove) and a treasure chest (unique elements).