我有一个数据框。
import pandas as pd
df = pd.DataFrame(
{'number': [0,0,0,1,1,2,2,2,2], 'id1': [100,100,100,300,400,700,700,800,700], 'id2': [100,100,200,500,600,700,800,900,1000]})
id1 id2 number
0 100 100 0
1 100 100 0
2 100 200 0
3 300 500 1
4 400 600 1
5 700 700 2
6 700 800 2
7 800 900 2
8 700 1000 2
我正在处理的数据框非常大,有数百万行。
我可以对一列应用groupby().unique
:
df.groupby(['number'])['id1'].unique()
number
0 [100]
1 [300, 400]
2 [700, 800]
Name: id1, dtype: object
df.groupby(['number'])['id2'].unique()
number
0 [100, 200]
1 [500, 600]
2 [700, 800, 900, 1000]
Name: id2, dtype: object
我想同时对两列进行唯一性操作,以使数据框按顺序排列:
number
0 [100, 200]
1 [300, 400, 500, 600]
2 [700, 800, 900, 1000]
当我尝试对两列进行此操作时,出现错误:
pd.Data.Frame(df.groupby(['number'])['id1', 'id2'].unique())
Traceback (most recent call last):
File "C:\Python34\lib\site-packages\IPython\core\interactiveshell.py", line 2885, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-15-bfc6026e241e>", line 9, in <module>
df.groupby(['number'])['id1', 'id2'].unique()
File "C:\Python34\lib\site-packages\pandas\core\groupby.py", line 498, in __getattr__
(type(self).__name__, attr))
AttributeError: 'DataFrameGroupBy' object has no attribute 'unique'
应该怎么做?使用多级索引是否更好?
编辑:另外,可以按照以下方式获取输出吗:
number
0 100
0 200
1 300
1 400
1 500
1 600
2 700
2 800
2 900
2 1000