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user432299
Asked: 2024-09-11 01:57:42 +0800 CST

Python Polars 样本 N-1（按组 ID 进行替换）

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我正在开展一个引导项目，需要对 M=N-1 个观测值进行放回抽样，其中 N 是特定组（由 group_id 定义）中唯一观测值的数量。我需要弄清楚如何在极坐标系中执行此操作。有什么解决方案吗？

这是一个展示我想要完成的事情的例子：

# Have:
water_data = {
    'group_id': [1,1,1,1,2,2,2,3,3,3,4,4,4,4,5,5,5],
    'obs_id_within_group': [1,2,3,4,1,2,3,1,2,3,1,2,3,4,1,2,3],
    'N': [4,4,4,4,3,3,3,3,3,3,4,4,4,4,3,3,3],
    'M': [3,3,3,3,2,2,2,2,2,2,3,3,3,3,2,2,2],
    'water_gallons': [12,23,21,11,10,10,10,23,24,25,27,30,17,12,11,14,20],
    'water_source': ['lake','lake','pond','river','lake','glacier','glacier','lake','pond','river','lake','lake','pond','river','river','lake','glacier'],
    'water_acidity': [3,4,5,1,2,4,3,2,3,3,4,6,7,8,8,3,1]
}
df=pl.DataFrame(water_data)
print(df)

# Want to randomly sample with replacement to:
sampled_water_data = {
    'group_id':            [1,1,1,2,2,3,3,4,4,4,5,5],
    'obs_id_within_group': [1,2,2,3,3,3,2,4,1,1,2,1],
    'N': [4,4,4,3,3,3,3,4,4,4,3,3],
    'M': [3,3,3,2,2,2,2,3,3,3,2,2],
    'water_gallons': [12,23,23,10,10,25,24,12,27,27,14,11],
    'water_source': ['lake','lake','lake','glacier','glacier','river','pond','river','lake','lake','lake','river'],
    'water_acidity': [3,4,4,3,3,3,3,8,4,4,5,8]
}
df_sampled=pl.DataFrame(sampled_water_data)
print(df_sampled)

不确定如何从每个组中抽取一个特定的数字。

python-polars

1 个回答

  1. Best Answer

    按 分组group_id，pl.len() - 1对行进行替换抽样，最后对除 之外的所有列进行分解group_id：

    df2 = (
    df.group_by("group_id")
    .agg(pl.all().sample(pl.len() - 1, with_replacement=True))
    .explode(pl.all().exclude("group_id"))
)

print(df2)

    输出：

    shape: (12, 7)
┌──────────┬─────────────────────┬─────┬─────┬───────────────┬──────────────┬───────────────┐
│ group_id ┆ obs_id_within_group ┆ N   ┆ M   ┆ water_gallons ┆ water_source ┆ water_acidity │
│ ---      ┆ ---                 ┆ --- ┆ --- ┆ ---           ┆ ---          ┆ ---           │
│ i64      ┆ i64                 ┆ i64 ┆ i64 ┆ i64           ┆ str          ┆ i64           │
╞══════════╪═════════════════════╪═════╪═════╪═══════════════╪══════════════╪═══════════════╡
│ 3        ┆ 2                   ┆ 3   ┆ 2   ┆ 25            ┆ river        ┆ 2             │
│ 3        ┆ 3                   ┆ 3   ┆ 2   ┆ 25            ┆ lake         ┆ 3             │
│ 5        ┆ 3                   ┆ 3   ┆ 2   ┆ 14            ┆ river        ┆ 3             │
│ 5        ┆ 3                   ┆ 3   ┆ 2   ┆ 14            ┆ lake         ┆ 8             │
│ 1        ┆ 2                   ┆ 4   ┆ 3   ┆ 21            ┆ lake         ┆ 3             │
│ 1        ┆ 2                   ┆ 4   ┆ 3   ┆ 12            ┆ river        ┆ 4             │
│ 1        ┆ 1                   ┆ 4   ┆ 3   ┆ 12            ┆ lake         ┆ 3             │
│ 4        ┆ 2                   ┆ 4   ┆ 3   ┆ 17            ┆ pond         ┆ 6             │
│ 4        ┆ 3                   ┆ 4   ┆ 3   ┆ 30            ┆ river        ┆ 7             │
│ 4        ┆ 1                   ┆ 4   ┆ 3   ┆ 12            ┆ lake         ┆ 8             │
│ 2        ┆ 2                   ┆ 3   ┆ 2   ┆ 10            ┆ glacier      ┆ 2             │
│ 2        ┆ 2                   ┆ 3   ┆ 2   ┆ 10            ┆ lake         ┆ 3             │
└──────────┴─────────────────────┴─────┴─────┴───────────────┴──────────────┴───────────────┘
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