使用Pandas数据帧不相交组进行随机抽样

Question

我需要通过属性将数据框随机分成两个不相交的集合'ids'.例如,请考虑以下数据框:

df=
Out[470]: 
          0     1     2     3       ids
0      17.0  18.0  16.0  15.0      13.0
1      18.0  16.0  15.0  15.0      13.0
2      16.0  15.0  15.0  16.0      13.0
131    12.0   8.0  21.0  19.0      14.0
132     8.0  21.0  19.0  20.0      14.0
133    21.0  19.0  20.0   9.0      14.0
248     NaN   NaN  12.0  11.0      17.0
249     NaN  12.0  11.0  10.0      17.0
250    12.0  11.0  10.0   NaN      17.0
287     3.0   3.0   1.0   8.0      20.0
288     3.0   1.0   8.0   3.0      20.0
289     1.0   8.0   3.0   3.0      20.0
413    21.0   7.0  16.0  18.0      25.0
414     7.0  16.0  18.0  19.0      25.0
415    16.0  18.0  19.0  18.0      25.0
665    10.0   8.0   8.0   7.0      27.0
666     8.0   8.0   7.0   9.0      27.0
667     8.0   7.0   9.0   8.0      27.0
790     NaN   NaN  15.0   NaN      33.0
791     NaN  15.0   NaN  10.0      33.0
792    15.0   NaN  10.0   NaN      33.0
812     NaN  16.0   NaN  17.0      34.0
813    16.0   NaN  17.0   NaN      34.0
814     NaN  17.0   NaN  13.0      34.0
944     3.0   4.0   3.0  18.0      35.0
945     4.0   3.0  18.0  18.0      35.0
946     3.0  18.0  18.0  11.0      35.0
1059    9.0  10.0   3.0   4.0      56.0
1060   10.0   3.0   4.0   3.0      56.0
1061    3.0   4.0   3.0   3.0      56.0
    ...   ...   ...   ...       ...
10125   NaN   9.0   5.0   5.0  101317.0
10126   9.0   5.0   5.0   5.0  101317.0
10127   5.0   5.0   5.0   7.0  101317.0

我需要得到两个(用一些分数大小随机分隔)数据帧,没有相交的值ids.

我知道如何以'非潘达式'方式解决它:

• 得到的独特价值 ids
• 随机将唯一值分成两个不相交的组
• 根据ids两组中的值使用选择行.isin()

我想知道是否有一个简单而巧妙的方法来做一些pandas内置函数,比如.sample()？

Answer 1

使用sklearn.model_selection.GroupShuffleSplit进行拆分:

from sklearn.model_selection import GroupShuffleSplit

# Initialize the GroupShuffleSplit.
gss = GroupShuffleSplit(n_splits=1, test_size=0.5)

# Get the indexers for the split.
idx1, idx2 = next(gss.split(df, groups=df.ids))

# Get the split DataFrames.
df1, df2 = df.iloc[idx1], df.iloc[idx2]