Pandas 在 groupby 之后获取所有行的最小值和最大值

Question

我有一个这样的数据框：

df = pd.DataFrame({'A' : list('ababababba'),
                   'B' : [1, 1, 1, 2, 2, 1,1,2,1,1],
                   'C' : [2.0, 5., 8., 1., 2., 9.,2.0,4.0,5.0,3.0],
                   'D' : [10,20,30,10,20,30,20,40,50,10]})

必填：

   A  B    C   D
0  a  1  2.0  10 # a1 min keep
1  b  1  5.0  20 # b1 min
2  a  1  8.0  30 # a1 max keep
3  b  2  1.0  10 
4  a  2  2.0  20
                  # b1 removed
                  # a1 remove
7  b  2  4.0  40
8  b  1  5.0  50 # b1 max keep
9  a  1  3.0  10 # a1 min keep

相关链接： Min and max row from pandas groupby

Max and min from two series in pandas groupby

Max and Min date in pandas groupby

pandas groupby and then select a row by value of column (min,max, for example)

Answer 1

你想要这个吗：

df.groupby(['A','B']).D.agg([min,max])

输出：

+---+---+-----+-----+
|   |   | min | max |
+---+---+-----+-----+
| A | B |     |     |
+---+---+-----+-----+
| a | 1 |  10 |  30 |
|   | 2 |  20 |  20 |
| b | 1 |  20 |  50 |
|   | 2 |  10 |  40 |
+---+---+-----+-----+

编辑：如果您想要所有行的最小值或最大值，请考虑transform

groups = df.groupby(['A','B']).D
min_val = groups.transform(min)
max_val = groups.transform(max)

df[(df.D==min_val) | (df.D==max_val)]

输出：

+---+---+---+-----+----+
|   | A | B |  C  | D  |
+---+---+---+-----+----+
| 0 | a | 1 | 2.0 | 10 |
| 1 | b | 1 | 5.0 | 20 |
| 2 | a | 1 | 8.0 | 30 |
| 3 | b | 2 | 1.0 | 10 |
| 4 | a | 2 | 2.0 | 20 |
| 7 | b | 2 | 4.0 | 40 |
| 8 | b | 1 | 5.0 | 50 |
+---+---+---+-----+----+