Pandas：在 groupby 之后重新整形/重新旋转数据框

Question

我在数据框的 duration 列上应用 quantile 函数：

a=df.groupby('version')[['duration']].quantile([.25, .5, .75])
a

                   duration
version     
4229        0.25    1451.00
            0.50    1451.00
            0.75    1451.00
6065        0.25     213.75
            0.50     426.50
            0.75     639.25
9209        0.25     386.50
            0.50     861.00
            0.75     866.00
2304        0.25     664.50
            0.50     669.00
            0.75     736.50
6389        0.25       1.00
            0.50     797.00
            0.75     832.00

我想知道如何 re-shape/re-pivot 上面的数据框，所以新的数据框（是的，它必须是数据框格式）看起来像：

version   duration_Q1    duration_Q2    duration_Q3

4429      1451.00        1451.00        1451.00
6065      213.75         426.50         639.25
9209      386.50         861.00         866.00
2304      664.50         669.00         736.50
6389      1.00           797.00         832.00

谢谢！

Answer 1

您可以使用 unstack，然后进行一些重命名操作

a = pd.DataFrame('duration': {(2304L, 0.25): 1565.6861959516361,
  (2304L, 0.5): 446.4769649280514,
  (2304L, 0.75): 701.8254115357969,
  (4229L, 0.25): 1868.982390749203,
  (4229L, 0.5): 242.36201172579996,
  (4229L, 0.75): 789.482292226787,
  (6065L, 0.25): 1421.9585894685038,
  (6065L, 0.5): 357.04491735326343,
  (6065L, 0.75): 169.78973203074895,
  (6389L, 0.25): 1789.1550141153925,
  (6389L, 0.5): 516.9365429825862,
  (6389L, 0.75): 1830.6493228794639,
  (9209L, 0.25): 1129.853279993191,
  (9209L, 0.5): 1759.1258334115485,
  (9209L, 0.75): 1499.0498929925702}}
)

pvt = a.unstack()
pvt.columns = pvt.columns.droplevel(0)
pvt.rename(columns={0.25:'duration_Q1',0.5:'duration_Q2',0.75:'duration_Q3'},inplace=True)

        duration_Q1  duration_Q2  duration_Q3
version                                       
2304     1565.686196   446.476965   701.825412
4229     1868.982391   242.362012   789.482292
6065     1421.958589   357.044917   169.789732
6389     1789.155014   516.936543  1830.649323
9209     1129.853280  1759.125833  1499.049893

Pandas：在 groupby 之后重新整形/重新旋转数据框

Pandas: re-shape/ re-pivot a data frame after groupby

pivot

reshape

python-3.x

pandas