例如,我有两个字典:
Dict A: {'a': 1, 'b': 2, 'c': 3}
Dict B: {'b': 3, 'c': 4, 'd': 5}
我需要一种python的方式来“组合”两个字典,这样的结果是:
{'a': 1, 'b': 5, 'c': 7, 'd': 5}
也就是说:如果一个键在两个字典中都出现,则将它们的值相加,如果它只在一个字典中出现,则保留其值。
例如,我有两个字典:
Dict A: {'a': 1, 'b': 2, 'c': 3}
Dict B: {'b': 3, 'c': 4, 'd': 5}
我需要一种python的方式来“组合”两个字典,这样的结果是:
{'a': 1, 'b': 5, 'c': 7, 'd': 5}
也就是说:如果一个键在两个字典中都出现,则将它们的值相加,如果它只在一个字典中出现,则保留其值。
当前回答
要获得更通用和可扩展的方法,请检查mergedict。它使用singledispatch,并可以根据类型合并值。
例子:
from mergedict import MergeDict
class SumDict(MergeDict):
@MergeDict.dispatch(int)
def merge_int(this, other):
return this + other
d2 = SumDict({'a': 1, 'b': 'one'})
d2.merge({'a':2, 'b': 'two'})
assert d2 == {'a': 3, 'b': 'two'}
其他回答
另外,请注意a.update(b)比a + b快2倍
from collections import Counter
a = Counter({'menu': 20, 'good': 15, 'happy': 10, 'bar': 5})
b = Counter({'menu': 1, 'good': 1, 'bar': 3})
%timeit a + b;
## 100000 loops, best of 3: 8.62 µs per loop
## The slowest run took 4.04 times longer than the fastest. This could mean that an intermediate result is being cached.
%timeit a.update(b)
## 100000 loops, best of 3: 4.51 µs per loop
来自python 3.5:合并和求和
Thanks to @tokeinizer_fsj that told me in a comment that I didn't get completely the meaning of the question (I thought that add meant just adding keys that eventually where different in the two dictinaries and, instead, i meant that the common key values should be summed). So I added that loop before the merging, so that the second dictionary contains the sum of the common keys. The last dictionary will be the one whose values will last in the new dictionary that is the result of the merging of the two, so I thing the problem is solved. The solution is valid from python 3.5 and following versions.
a = {
"a": 1,
"b": 2,
"c": 3
}
b = {
"a": 2,
"b": 3,
"d": 5
}
# Python 3.5
for key in b:
if key in a:
b[key] = b[key] + a[key]
c = {**a, **b}
print(c)
>>> c
{'a': 3, 'b': 5, 'c': 3, 'd': 5}
可重用代码
a = {'a': 1, 'b': 2, 'c': 3}
b = {'b': 3, 'c': 4, 'd': 5}
def mergsum(a, b):
for k in b:
if k in a:
b[k] = b[k] + a[k]
c = {**a, **b}
return c
print(mergsum(a, b))
更传统的结合两个字典的方法。使用模块和工具是很好的,但理解背后的逻辑将有助于防止你不记得工具。
程序组合两个字典相加值的公共键。
def combine_dict(d1,d2):
for key,value in d1.items():
if key in d2:
d2[key] += value
else:
d2[key] = value
return d2
combine_dict({'a':1, 'b':2, 'c':3},{'b':3, 'c':4, 'd':5})
output == {'b': 5, 'c': 7, 'd': 5, 'a': 1}
这是一个很一般的解。你可以处理任意数量的dict +键,只在一些dict +容易使用任何聚合函数你想要:
def aggregate_dicts(dicts, operation=sum):
"""Aggregate a sequence of dictionaries using `operation`."""
all_keys = set().union(*[el.keys() for el in dicts])
return {k: operation([dic.get(k, None) for dic in dicts]) for k in all_keys}
例子:
dicts_same_keys = [{'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 2, 'y': 3}]
aggregate_dicts(dicts_same_keys, operation=sum)
#{'x': 3, 'y': 6}
不相同的键和泛型聚合示例:
dicts_diff_keys = [{'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 2, 'y': 3, 'c': 4}]
def mean_no_none(l):
l_no_none = [el for el in l if el is not None]
return sum(l_no_none) / len(l_no_none)
aggregate_dicts(dicts_diff_keys, operation=mean_no_none)
# {'x': 1.0, 'c': 4.0, 'y': 2.0}
一种解决方法是使用字典理解。
C = { k: A.get(k,0) + B.get(k,0) for k in list(B.keys()) + list(A.keys()) }