Is there a simple way to index all elements of a list (or array, or whatever) except for a particular index? E.g.,
mylist[3]will return the item in position 3milist[~3]will return the whole list except for 3
For a list, you could use a list comp. For example, to make b a copy of a without the 3rd element:
a = range(10)[::-1] # [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
b = [x for i,x in enumerate(a) if i!=3] # [9, 8, 7, 5, 4, 3, 2, 1, 0]
This is very general, and can be used with all iterables, including numpy arrays. If you replace [] with (), b will be an iterator instead of a list.
Or you could do this in-place with pop:
a = range(10)[::-1] # a = [9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
a.pop(3) # a = [9, 8, 7, 5, 4, 3, 2, 1, 0]
In numpy you could do this with a boolean indexing:
a = np.arange(9, -1, -1) # a = array([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])
b = a[np.arange(len(a))!=3] # b = array([9, 8, 7, 5, 4, 3, 2, 1, 0])
which will, in general, be much faster than the list comprehension listed above.
If you are using numpy, the closest, I can think of is using a mask
>>> import numpy as np
>>> arr = np.arange(1,10)
>>> mask = np.ones(arr.shape,dtype=bool)
>>> mask[5]=0
>>> arr[mask]
array([1, 2, 3, 4, 5, 7, 8, 9])
Something similar can be achieved using itertools without numpy
>>> from itertools import compress
>>> arr = range(1,10)
>>> mask = [1]*len(arr)
>>> mask[5]=0
>>> list(compress(arr,mask))
[1, 2, 3, 4, 5, 7, 8, 9]
Use np.delete ! It does not actually delete anything inplace
Example:
import numpy as np
a = np.array([[1,4],[5,7],[3,1]])
# a: array([[1, 4],
# [5, 7],
# [3, 1]])
ind = np.array([0,1])
# ind: array([0, 1])
# a[ind]: array([[1, 4],
# [5, 7]])
all_except_index = np.delete(a, ind, axis=0)
# all_except_index: array([[3, 1]])
# a: (still the same): array([[1, 4],
# [5, 7],
# [3, 1]])
I'm going to provide a functional (immutable) way of doing it.
The standard and easy way of doing it is to use slicing:
index_to_remove = 3
data = [*range(5)]
new_data = data[:index_to_remove] + data[index_to_remove + 1:]
print(f"data: {data}, new_data: {new_data}")
Output:
data: [0, 1, 2, 3, 4], new_data: [0, 1, 2, 4]
Use list comprehension:
data = [*range(5)]
new_data = [v for i, v in enumerate(data) if i != index_to_remove]
print(f"data: {data}, new_data: {new_data}")
Output:
data: [0, 1, 2, 3, 4], new_data: [0, 1, 2, 4]
Use filter function:
index_to_remove = 3
data = [*range(5)]
new_data = [*filter(lambda i: i != index_to_remove, data)]
Output:
data: [0, 1, 2, 3, 4], new_data: [0, 1, 2, 4]
Using masking. Masking is provided by itertools.compress function in the standard library:
from itertools import compress
index_to_remove = 3
data = [*range(5)]
mask = [1] * len(data)
mask[index_to_remove] = 0
new_data = [*compress(data, mask)]
print(f"data: {data}, mask: {mask}, new_data: {new_data}")
Output:
data: [0, 1, 2, 3, 4], mask: [1, 1, 1, 0, 1], new_data: [0, 1, 2, 4]
Use itertools.filterfalse function from Python standard library
from itertools import filterfalse
index_to_remove = 3
data = [*range(5)]
new_data = [*filterfalse(lambda i: i == index_to_remove, data)]
print(f"data: {data}, new_data: {new_data}")
Output:
data: [0, 1, 2, 3, 4], new_data: [0, 1, 2, 4]