与列中的计数成比例地对 Pandas 数据框的行进行采样 [英] Sample rows of pandas dataframe in proportion to counts in a column

问题描述

我有一个大约有 10,000,000 行的大熊猫数据框.每个代表一个特征向量.特征向量以自然组的形式出现，组标签位于名为 group_id 的列中.我想随机抽样 10% 说的行，但与每个 group_id 的数量成比例.

I have a large pandas dataframe with about 10,000,000 rows. Each one represents a feature vector. The feature vectors come in natural groups and the group label is in a column called group_id. I would like to randomly sample 10% say of the rows but in proportion to the numbers of each group_id.

例如，如果 group_id's 是 A, B, A, C, A, B 那么我希望我的一半采样行具有 group_id A，六分之二有 group_id B 六分之一有 group_id C.

For example, if the group_id's are A, B, A, C, A, B then I would like half of my sampled rows to have group_id A, two sixths to have group_id B and one sixth to have group_id C.

我可以看到熊猫函数sample 但我不确定如何使用它来实现这一目标.

I can see the pandas function sample but I am not sure how to use it to achieve this goal.

推荐答案

可以使用groupby和sample

You can use groupby and sample

sample_df = df.groupby('group_id').apply(lambda x: x.sample(frac=0.1))

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