def multi_group_by_as_map(self, key=None):
from .map import Map
key_to_grp = defaultdict(list)
for elem in self:
for k in key(elem):
key_to_grp[k].append(elem)
return Map(key_to_grp)
def group_by_as_map(self, key_func=None):
'''Group values in to a Map by the value of key function evaluation
result.
Comparing to ``group_by_as_stream``, there're some pros and cons.
Pros:
* Elements don't need to be sorted by the key function first.
You can call ``map_group_by`` anytime and correct grouping result.
Cons:
* Key function has to be evaluated to a hashable value.
* Not Lazy-evaluating. Consume more memory while grouping.
Yield a group as soon as possible.
>>> Stream.range(10).group_by_as_map(key_func=lambda n: n % 3)
Map({0: Array([0, 3, 6, 9]), 1: Array([1, 4, 7]), 2: Array([2, 5, 8])})
'''
from .map import Map
key_to_grp = defaultdict(Array)
for elem in self:
key_to_grp[key_func(elem)].append(elem)
return Map(key_to_grp)
def value_counts(self):
'''Get a Counter instance of elements counts
Returns
-------
Map[E, int]
'''
from carriage import Map
return Map(Counter(self))
def to_map(self):
'''Convert to a Map
>>> Stream.range(5, 10, 2).zip_index().to_map()
Map({5: 0, 7: 1, 9: 2})
Returns
-------
Map
'''
from .map import Map
return Map(self)