两列的 Frozenset 并集

Question

我有一个数据集包含两列冻结集。现在我想 merge/take 合并这些 frozensets。我可以使用 for 循环执行此操作，但是我的数据集包含 > 2700 万行，因此我正在寻找一种避免 for 循环的方法。大家有什么想法吗？

数据

import pandas as pd
import numpy as np
d = {'ID1': [frozenset(['a', 'b']), frozenset(['a','c']), frozenset(['c','d'])],
    'ID2': [frozenset(['c', 'g']), frozenset(['i','f']), frozenset(['t','l'])]}
df = pd.DataFrame(data=d)

for循环代码

from functools import reduce
df['frozenset']=0
for i in range(len(df)):
    df['frozenset'].iloc[i] = reduce(frozenset.union, [df['ID1'][i],df['ID2'][i]])

期望输出

    ID1      ID2     frozenset
0   (a, b)  (c, g)  (a, c, g, b)
1   (a, c)  (f, i)  (a, c, f, i)
2   (c, d)  (t, l)  (c, d, t, l)

Answer 1

你可以试试：

import pandas as pd
import numpy as np

d = {'ID1': [frozenset(['a', 'b']), frozenset(['a','c']), frozenset(['c','d'])],
    'ID2': [frozenset(['c', 'g']), frozenset(['i','f']), frozenset(['t','l'])]}
df = pd.DataFrame(data=d)
from functools import reduce
df['frozenset']=0

add = []
for i in range(len(df)):
    df['frozenset'].iloc[i] = reduce(frozenset.union, [df['ID1'][i],df['ID2'][i]])
add.append(df)
print(add)

Answer 2

您似乎不需要在此处使用 functools.reduce。与每对 frozensets 直接联合就足够了。

如果您想要此类操作的最快速度，我建议您查看列表推导（详尽的讨论请参阅）。

df['union'] = [x | y for x, y in zip(df['ID1'], df['ID2'])]
df

      ID1     ID2         union
0  (a, b)  (c, g)  (c, a, b, g)
1  (c, a)  (f, i)  (c, a, i, f)
2  (c, d)  (l, t)  (c, l, d, t)

如果您希望这对多列进行概括，您可以使用 frozenset.union() 将它们全部合并。

df['union2'] = [frozenset.union(*X) for X in df[['ID1', 'ID2']].values]
df

      ID1     ID2         union        union2
0  (a, b)  (c, g)  (c, a, b, g)  (c, a, b, g)
1  (c, a)  (f, i)  (c, a, i, f)  (c, a, i, f)
2  (c, d)  (l, t)  (c, l, d, t)  (c, l, d, t)

两列的 Frozenset 并集

Frozenset union of two columns

python

pandas

union

frozenset