Python中的分组/聚类数字

Grouping / clustering numbers in Python(Python中的分组/聚类数字)

问题描述

我用谷歌搜索过，我已经测试过，这让我束手无策.我有一个需要按相似度分组的数字列表.例如，在 [1, 6, 9, 100, 102, 105, 109, 134, 139] 的列表中，将 1 6 9 放入列表中，将 100、102、105 和 109 放入列表中列表，以及 134 和 139.我的数学很糟糕，我已经尝试过这个，但我无法让它工作.为了尽可能明确，我希望将彼此相距 10 个值以内的数字分组.任何人都可以帮忙吗?谢谢.

I've googled, I've tested, and this has me at my wits end. I have a list of numbers I need to group by similarity. For instance, in a list of [1, 6, 9, 100, 102, 105, 109, 134, 139], 1 6 9 would be put into a list, 100, 102, 105, and 109 would be put into a list, and 134 and 139. I'm terrible at math, and I've tried and tried this, but I can't get it to work. To be explicit as possible, I wish to group numbers that are within 10 values away from one another. Can anyone help? Thanks.

推荐答案

集群分析有很多方法.一种简单的方法是查看连续数据元素之间的间隙大小:

There are many ways to do cluster analysis. One simple approach is to look at the gap size between successive data elements:

def cluster(data, maxgap):
    '''Arrange data into groups where successive elements
       differ by no more than *maxgap*

        >>> cluster([1, 6, 9, 100, 102, 105, 109, 134, 139], maxgap=10)
        [[1, 6, 9], [100, 102, 105, 109], [134, 139]]

        >>> cluster([1, 6, 9, 99, 100, 102, 105, 134, 139, 141], maxgap=10)
        [[1, 6, 9], [99, 100, 102, 105], [134, 139, 141]]

    '''
    data.sort()
    groups = [[data[0]]]
    for x in data[1:]:
        if abs(x - groups[-1][-1]) <= maxgap:
            groups[-1].append(x)
        else:
            groups.append([x])
    return groups

if __name__ == '__main__':
    import doctest
    print(doctest.testmod())

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