Python Pandas从Groupby中选择组的随机样本

Python Pandas从Groupby中选择组的随机样本

您可以对的唯一值进行随机抽样，将其

df.some_key.unique()

用于对进行切片

df

，最后

groupby

对结果进行切片：

In [337]:df = pd.Dataframe({'some_key': [0,1,2,3,0,1,2,3,0,1,2,3],        'val':      [1,2,3,4,1,5,1,5,1,6,7,8]})In [338]:print df[df.some_key.isin(random.sample(df.some_key.unique(),2))].groupby('some_key').mean()    valsome_key          0         1.0000002         3.666667

如果有多个groupby键：

In [358]:df = pd.Dataframe({'some_key1':[0,1,2,3,0,1,2,3,0,1,2,3],        'some_key2':[0,0,0,0,1,1,1,1,2,2,2,2],        'val':      [1,2,3,4,1,5,1,5,1,6,7,8]})In [359]:gby = df.groupby(['some_key1', 'some_key2'])In [360]:print gby.mean().ix[random.sample(gby.indices.keys(),2)]          valsome_key1 some_key2     1         1 53         2 8

但是，如果您只是要获取每个组的值，则甚至不需要

groubpy

，它

MultiIndex

会做：

In [372]:idx = random.sample(set(pd.MultiIndex.from_product((df.some_key1, df.some_key2)).tolist()),         2)print df.set_index(['some_key1', 'some_key2']).ix[idx]          valsome_key1 some_key2     2         0 33         1 5