利用Python进行采样的几种方式

最新推荐文章于 2024-01-14 00:30:52 发布

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最新推荐文章于 2024-01-14 00:30:52 发布 · 1.2w 阅读

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#Python采样

本文介绍了Python中三种常用的采样方法：1) 使用random.sample从序列中无放回地抽取固定数量的元素；2) 利用numpy.random.choice进行有放回或无放回的随机抽样，并可设置概率分布；3) pandas.DataFrame.sample允许从DataFrame中抽取行，支持替换、权重和随机种子等选项。

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1) random.sample(population,k)：

    Chooses k unique random elements from a population sequence or set.
    
    Returns a new list containing elements from the population while
    leaving the original population unchanged.  The resulting list is
    in selection order so that all sub-slices will also be valid random
    samples.  This allows raffle winners (the sample) to be partitioned
    into grand prize and second place winners (the subslices).
    
    Members of the population need not be hashable or unique.  If the
    population contains repeats, then each occurrence is a possible
    selection in the sample.
    
    To choose a sample in a range of integers, use range as an argument.
    This is especially fast and space efficient for sampling from a
    large population:   sample(range(10000000), 60)

2) numpy.random.choice(a,size=None,replace=None,p=None)：