根据熊猫中其他列的交集加入列中的唯一值答案

【问题标题】：Join unique values in a column based on intersection of other columns in pandas根据熊猫中其他列的交集加入列中的唯一值
【发布时间】：2023-01-03 14:21:47
【问题描述】：

可以说我有以下数据框：

df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
                         "bar", "bar", "bar", "bar","bar"],
                   "B": ["one", "one", "one", "two", "two",
                         "one", "one", "two", "two","two"],
                   "C": ["small", "large", "large", "small",
                         "small", "large", "small", "small",
                         "large", "large"],
                   "D": [1, 2, 3, 4, 5, 6, 7, 8, 9,99999]})

如果 "A"、"B" 和 "C" 中的值存在交集，我想在 "D" 列中加入（连接？或合并？）值。通过交集，我的意思是我想要这个 DataFrame：

    A   B   C   D
0   foo one small   1
1   foo one large   2,3
2   foo two small   4,5
3   bar one large   6
4   bar one small   7
5   bar two small   8
6   bar two large   9,99999

有最小、最大、总和等聚合函数，但我根本想不出解决方案。

【问题讨论】：

标签： python pandas dataframe

【解决方案1】：

采用：

df1 = (df.assign(D = df.D.astype(str))
        .groupby(['A','B','C'], sort=False)['D']
        .agg(','.join)
        .reset_index())
print (df1)
     A    B      C        D
0  foo  one  small        1
1  foo  one  large      2,3
2  foo  two  small      4,5
3  bar  one  large        6
4  bar  one  small        7
5  bar  two  small        8
6  bar  two  large  9,99999

要么：

df1 = (df.groupby(['A','B','C'], sort=False)['D']
        .agg(lambda x: ','.join(x.astype(str)))
        .reset_index())
print (df1)
     A    B      C        D
0  foo  one  small        1
1  foo  one  large      2,3
2  foo  two  small      4,5
3  bar  one  large        6
4  bar  one  small        7
5  bar  two  small        8
6  bar  two  large  9,99999

如果可能的话，每组 D 中的重复值：

df2 = (df.groupby(['A','B','C'], sort=False)['D']
        .agg(lambda x: ','.join(x.astype(str).unique()))
        .reset_index())

【讨论】：