pd.qcut-ValueError:容器边缘必须唯一

问题描述

我的数据是此处.

q = pd.qcut(df['loss_percent'], 10)

ValueError: Bin edges must be unique: array([ 0.38461538,  0.38461538,  0.46153846,  0.46153846,  0.53846154,
        0.53846154,  0.53846154,  0.61538462,  0.69230769,  0.76923077,  1.        ])

我已阅读为什么使用-pandas-qcut-return-valueerror ，但是我仍然感到困惑.

I have read through why-use-pandas-qcut-return-valueerror, however I am still confused.

我想象我的一个值出现的频率很高，并且破坏了qcut.

I imagine that one of my values has a high frequency of occurrence and that is breaking qcut.

首先，步骤是如何确定是否确实如此，以及哪个值是问题所在.最后，对于我的数据，哪种解决方案是合适的.

First, step is how do I determine if that is indeed the case, and which value is the problem. Lastly, what kind of solution is appropriate given my data.

推荐答案

在帖子 https://stackoverflow.com中使用解决方案/a/36883735/2336654

def pct_rank_qcut(series, n):
    edges = pd.Series([float(i) / n for i in range(n + 1)])
    f = lambda x: (edges >= x).argmax()
    return series.rank(pct=1).apply(f)

q = pct_rank_qcut(df.loss_percent, 10)

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