我有一個字典列表如下：rois = [{'player': 'kraftvk', 'over': {1.5: 67.97, 1.75: 51.005}, 'under': {1.5: -77.97, 1.75: -59.12}}, {'player': 'meltosik', 'over': {1.5: 61.635, 1.75: 37.455}, 'under': {1.5: -71.635, 1.75: -44.765}}]我想得到每本字典的平均值。預期輸出：d = {'over': {1.5: 64.80, 1.75: 44.23}, 'under': {1.5: -74.80, 1.75: -51.9425}}因此，映射每個字典中每個鍵的值并將它們平均并放入新字典中。不確定這樣做的最佳/最pythonic方式。第一個列表的結構與第二個列表的結構相同，所以可以這樣做：d = {'over': {}, 'under': {}}for k,v in rois[0].items(): if k != 'player': for quote, roi in rois[0][k].items(): if k == 'over': d[k][quote] = (roi + rois[1]['over'][quote])/2 if k == 'under': d[k][quote] = (roi + rois[1]['under'][quote])/2這似乎有點矯枉過正，可能有比這更優雅的解決方案。幫助表示贊賞。
3 回答
MMMHUHU
TA貢獻1834條經驗 獲得超8個贊
可以爭論它們是否更“Pythonic”，但字典理解是一種選擇。zip()這是一種使用字典理解和內置map()函數的方法
>>> rois = [{'player': 'kraftvk', 'over': {1.5: 67.97, 1.75: 51.005}, 'under': {1.5: -77.97, 1.75: -59.12}}, {'player': 'meltosik', 'over': {1.5: 61.635, 1.75: 37.455}, 'under': {1.5: -71.635, 1.75: -44.765}}]
>>> d1 = { key : zip(*[ elem[key].values() for elem in rois]) for key in rois[0].keys() if key != "player" }
>>> d2 = { key : value.keys() for key,value in rois[0].items() if key != "player" }
>>> avg = lambda l : round(sum(l)/float(len(l)), 2)
>>> d3 = { key : map(avg, value) for key, value in d1.items() }
>>> d = { key : dict(zip(value, d3[key])) for key, value in d2.items() }
>>> d
{'under': {1.5: -74.8, 1.75: -51.94}, 'over': {1.5: 64.8, 1.75: 44.23}}
UYOU
TA貢獻1878條經驗 獲得超4個贊
您可以使用Counter查找所有 dict 值的總和，然后最后將其除以列表的長度以獲得平均值
from collections import Counter
cover = Counter(); cunder = Counter()
for d in rois:
cover.update(d['over'])
cunder.update(d['under'])
>>> l = len(rois)
>>> res = {}
>>> res['over'] = {k:round(v/l,2) for k,v in cover.items()}
>>> res['under'] = {k:round(v/l,2) for k,v in cunder.items()}
>>>
>>> res
{'over': {1.5: 64.8, 1.75: 44.23}, 'under': {1.5: -74.8, 1.75: -51.94}}
ibeautiful
TA貢獻1993條經驗 獲得超6個贊
d = {'over': [], 'under': []}
rois = [{'player': 'kraftvk', 'over': {1.5: 67.97, 1.75: 51.005}, 'under': {1.5: -77.97, 1.75: -59.12}}, {'player': 'meltosik', 'over': {1.5: 61.635, 1.75: 37.455}, 'under': {1.5: -71.635, 1.75: -44.765}}]
# Collecting players 'over' and 'under' dictionaries
for player_dict in rois:
d['over'].append(player_dict['over'])
d['under'].append(player_dict['under'])
print(d)
s = {'over': {}, 'under': {}}
def average_dicts(dicts):
sum_dict = {}
# Going over the ['over' and 'under'] dictionaries collection
for d in dicts:
# Going over the [{1.5 : value_1, 1.75 : value_2}] dictionary, that's under either ['over' and 'under'] dictionaries
for k, v in d.items():
# Summing all values of either [ 1.5, 1.75]
if k not in sum_dict.keys():
sum_dict[k] = 0
sum_dict[k] += d.get(k,0)
# Dividing sum by number of dictionaries to get average
for k, v in sum_dict.items():
sum_dict[k] = v / len(dicts)
return sum_dict
s['over'] = average_dicts(d['over'])
s['under'] = average_dicts(d['under'])
print(s)
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