How to remove multiple indexes from a list at the same time? [duplicate]

Solution 1:

You need to do this in a loop, there is no built-in operation to remove a number of indexes at once.

Your example is actually a contiguous sequence of indexes, so you can do this:

del my_list[2:6]

which removes the slice starting at 2 and ending just before 6.

It isn't clear from your question whether in general you need to remove an arbitrary collection of indexes, or if it will always be a contiguous sequence.

If you have an arbitrary collection of indexes, then:

indexes = [2, 3, 5]
for index in sorted(indexes, reverse=True):
    del my_list[index]

Note that you need to delete them in reverse order so that you don't throw off the subsequent indexes.

Solution 2:

remove_indices = [1,2,3]
somelist = [i for j, i in enumerate(somelist) if j not in remove_indices]

Example:

In [9]: remove_indices = [1,2,3]

In [10]: somelist = range(10)

In [11]: somelist = [i for j, i in enumerate(somelist) if j not in remove_indices]

In [12]: somelist
Out[12]: [0, 4, 5, 6, 7, 8, 9]

Solution 3:

There wasn't much hint on performance for the different ways so I performed a test on removing 5000 items from 50000 in all 3 generally different approaches, and for me numpy was the winner (if you have elements that fit in numpy):

• 7.5 sec for the enumerated list comprehension [4.5 sec on another PC]
• 0.08 sec for deleting items in reverse order [0.017 (!) sec]
• 0.009 sec for numpy.delete [0.006 sec]

Here's the code I timed (in the third function conversion from/to list may be removed if working directly on numpy arrays is ok):

import time
import numpy as np
import random

def del_list_indexes(l, id_to_del):
    somelist = [i for j, i in enumerate(l) if j not in id_to_del]
    return somelist

def del_list_inplace(l, id_to_del):
    for i in sorted(id_to_del, reverse=True):
        del(l[i])

def del_list_numpy(l, id_to_del):
    arr = np.array(l, dtype='int32')
    return list(np.delete(arr, id_to_del))

l = range(50000)
random.shuffle(l)
remove_id = random.sample(range(len(l)), 5000) # 10% ==> 5000

# ...

Solution 4:

If you can use numpy, then you can delete multiple indices:

>>> import numpy as np
>>> a = np.arange(10)
>>> np.delete(a,(1,3,5))
array([0, 2, 4, 6, 7, 8, 9])

and if you use np.r_ you can combine slices with individual indices:

>>> np.delete(a,(np.r_[0:5,7,9]))
array([5, 6, 8])

However, the deletion is not in place, so you have to assign to it.