Question

我是编程新手，如果有人可以在Python / Pandas中提供以下帮助，我将不胜感激。我有一个列表作为值列表。我希望能够将具有相似值的键组合在一起。我在这里看到过类似的问题，但在这种情况下的问题是我想忽略值的顺序，例如：

classmates={'jack':['20','male','soccer'],'brian':['26','male','tennis'],'charles':['male','soccer','20'],'zulu':['19','basketball','male']}

jack和charles具有相同的值，但顺序不同。我想要一个输出，无论顺序如何都会给出值。在这种情况下，输出将被写入csv

['20','male','soccer']: jack, charles
['26','male','tennis']: brian
['19','basketball','male']: zulu

Answer 1

使用frozensets，apply，groupby + agg：

s = pd.DataFrame(classmates).T.apply(frozenset, 1)

s2 = pd.Series(s.index.values, index=s)\
          .groupby(level=0).agg(lambda x: list(x))

s2
(soccer, 20, male)        [charles, jack]
(26, male, tennis)                [brian]
(basketball, male, 19)             [zulu]
dtype: object

Answer 2

您可以使用以下代码以您希望的方式反转字典：

classmates={'jack':['20','male','soccer'],'brian':['26','male','tennis'],'charles':['male','soccer','20'],'zulu':['19','basketball','male']}

out_dict = {}
for key, value in classmates.items():
    current_list = out_dict.get(tuple(sorted(value)), [])
    current_list.append(key)
    out_dict[tuple(sorted(value))] = current_list

print(out_dict)

打印

{('20', 'male', 'soccer'): ['charles', 'jack'], ('26', 'male', 'tennis'): ['brian'], ('19', 'basketball', 'male'): ['zulu']}

Answer 3

from collections import defaultdict

ans = defaultdict(list)

classmates={'jack':['20','male','soccer'],
            'brian':['26','male','tennis'],
            'charles':['male','soccer','20'],
            'zulu':['19','basketball','male']
           }


for k, v in classmates.items():
    sorted_tuple = tuple(sorted(v))
    ans[sorted_tuple].append(k)

# ans is: a dict you desired
# defaultdict(<class 'list'>, {('20', 'male', 'soccer'): ['jack','charles'],
# ('26', 'male', 'tennis'): ['brian'], ('19', 'basketball', 'male'): ['zulu']})

for k, v in ans.items():
    print(k, ':', v)

# output: 
# ('20', 'male', 'soccer') : ['jack', 'charles']
# ('26', 'male', 'tennis') : ['brian']
# ('19', 'basketball', 'male') : ['zulu']

Answer 4

首先将字典转换为pandas数据帧。

df= pd.DataFrame.from_dict(classmates,orient='index')

然后按年龄按升序排序。

df=df.sort_values(by=0,ascending=True)

这里0是默认列名。您可以重命名此列名称。

Answer 5

您可以在一行中执行此操作：

print({tuple(sorted(v)) : [k for k,vv in a.items() if sorted(vv) == sorted(v)] for v in a.values()})

或

以下是详细解决方案：

dict_1 = {'jack': ['20', 'male', 'soccer'], 'brian': ['26', 'male', 'tennis'], 'charles': ['male', 'soccer', '20'],
     'zulu': ['19', 'basketball', 'male']}

sorted_dict = {}
for key,value in dict_1.items():
    sorted_1 = sorted(value)
    sorted_dict[key] = sorted_1

tracking_of_duplicate = []
final_dict = {}
for key1,value1 in sorted_dict.items():
    if value1 not in tracking_of_duplicate:
        tracking_of_duplicate.append(value1)
        final_dict[tuple(value1)] = [key1]

    else:

        final_dict[tuple(value1)].append(key1)

print(final_dict)

在字典中对相似值进行分组

5 个答案: