熊猫在groupby之后获得所有的最大值和最小值行

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

您想要这个吗？

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：如果要使所有行都具有最小值或最大值，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 |
+---+---+---+-----+----+