I would like to index a list with another list like this
L = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
Idx = [0, 3, 7]
T = L[ Idx ]
and T should end up being a list containing ['a', 'd', 'h'].
Is there a better way than
T = []
for i in Idx:
T.append(L[i])
print T
# Gives result ['a', 'd', 'h']
T = [L[i] for i in Idx]
If you are using numpy, you can perform extended slicing like that:
>>> import numpy
>>> a=numpy.array(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
>>> Idx = [0, 3, 7]
>>> a[Idx]
array(['a', 'd', 'h'],
dtype='|S1')
...and is probably much faster (if performance is enough of a concern to to bother with the numpy import)
list with np.array, but np.append did not work correctly (i.e. the same results as for lists) when the elements themselves were jagged arrays.T = map(lambda i: L[i], Idx)
I wasn't happy with any of these approaches, so I came up with a Flexlist class that allows for flexible indexing, either by integer, slice or index-list:
class Flexlist(list):
def __getitem__(self, keys):
if isinstance(keys, (int, slice)): return list.__getitem__(self, keys)
return [self[k] for k in keys]
Which, for your example, you would use as:
L = Flexlist(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'])
Idx = [0, 3, 7]
T = L[ Idx ]
print(T) # ['a', 'd', 'h']
existing_list = Flexlist(existing_list) and we have the required functionality without breaking any codeself[int(k)] instead, so that I could use np.arrays as indices too. Otherwise, you will get an np.int64 is not iterable error.
return Flexlist([self[k] for k in keys]) and isinstance(keys, (int, np.integer, slice)) so you can work with numpy integer types for indexing.A functional approach:
a = [1,"A", 34, -123, "Hello", 12]
b = [0, 2, 5]
from operator import itemgetter
print(list(itemgetter(*b)(a)))
[1, 34, 12]
b happens to contain just one item.You could also use the __getitem__ method combined with map like the following:
L = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
Idx = [0, 3, 7]
res = list(map(L.__getitem__, Idx))
print(res)
# ['a', 'd', 'h']
L= {'a':'a','d':'d', 'h':'h'}
index= ['a','d','h']
for keys in index:
print(L[keys])
I would use a Dict add desired keys to index
My problem: Find indexes of list.
L = makelist() # Returns a list of different objects
La = np.array(L, dtype = object) # add dtype!
for c in chunks:
L_ = La[c] # Since La is array, this works.
L[idx]doesn't just work in base Python. Zen of python and all that. In numpy, things like this work just fine.L[idx]did do this in base Python. In fact, I can quote the Zen of Python to support that: "Special cases aren't special enough to break the rules."L[idx]does "work" - it means that the tuple(0, 3, 7)will be supplied as an index, which will subsequently cause aTypeError. It would work fine with, say, a dict using tuples for its keys. (Slices are different, in that - in prehistoric times - they were a special syntax before there was aslicetype.)