以上数据帧是通过以下代码生成的:
$this->uri->segment(5)
我使用以下代码从Pandas Dataframe(duplicateProductList(如上所示))生成了一个字典:
errors.add(:base, "check no imports")
上面的代码片段产生以下字典:
newCols = ['Book-1', 'Book-2', 'Similarity Score']
l1 = ['b1', 'b1', 'b2']
l2 = ['b2', 'b3', 'b3']
score1 = [0.95, 0.87, 0.84]
duplicateProductList = pd.DataFrame(columns=newCols)
duplicateProductList['Book-1'] = l1
duplicateProductList['Book-2'] = l2
duplicateProductList['Similarity Score'] = score1
print(duplicateProductList)
相反,我想产生以下字典:
from collections import defaultdict
new_dict = {}
my_list = [(i,[a,b]) for i, a,b in zip(duplicateProductList['Book-1'], duplicateProductList['Book-2'], duplicateProductList['Similarity Score'])]
for (key, value) in my_list:
if key in new_dict:
new_dict[key].append(value)
else:
new_dict[key] = [value]
print(new_dict)
有人可以帮助我修改字典理解以产生上述字典吗?
答案 0 :(得分:2)
>>> import collections
>>> from pprint import pprint
>>> df
Book-1 Book-2 Similarity Score
0 b1 b2 0.95
1 b1 b3 0.87
2 b2 b3 0.84
>>>
>>> d = collections.defaultdict(list)
>>> for row in df.itertuples(index=False):
a,b,c = row
d[a].append((b,c))
d[b].append((a,c))
>>> pprint(d)
defaultdict(<class 'list'>,
{'b1': [('b2', 0.95), ('b3', 0.87)],
'b2': [('b1', 0.95), ('b3', 0.84)],
'b3': [('b1', 0.87), ('b2', 0.84)]})