from collections import defaultdict

def split_d(d, key):
  include = defaultdict(list)
  exclude = defaultdict(list)

  for i in range(0, len(d[key])):
    binary = d[key][i]
    for k, v in d.items():
      if k == key:
        continue

      if binary == 0:
        exclude[k].append(v[i])
      elif binary == 1:
        include[k].append(v[i])
      else:
        raise ValueError(f"Key {key} is not binary. Expected values 0 or 1")

  return include, exclude

d = {
  'prof': [1,0,0,1,1,1,1,1,0,1],
  'val': [45,12,36,48,48,59,5,4,32,7]
}

print(split_d(d, 'prof'))

import itertools

def split_d(d, key, val):
    assert set(d[key]) == {0, 1}
    sorted_tuples = sorted(zip(d[key], d[val]), key=lambda x: x[0])
    grouped = itertools.groupby(sorted_tuples, lambda x: x[0])
    return [{'val': [x[1] for x in g]} for _, g in grouped]

In [52]: %timeit split_d_g(d, 'prof', 'val')
5.63 µs ± 68.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

In [53]: %timeit split_d_op(d, 'prof')
6.82 µs ± 597 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)