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Pandas.cut 指定自定义范围

[英]Pandas.cut specify custom range

原文 2019-02-10 03:18:05 1 1 python/ pandas

Is it possible to specify a custom range in pandas.cut ?是否可以在pandas.cut指定自定义范围？

I have a dataset where I need to bin the age column (and several other columns).我有一个数据集，我需要将年龄列（和其他几个列）合并到其中。 The min and the max value of age in the dataset is 18 and 55 , respectively.数据集中age的min和max分别为18和55 。 However, in the documentation of the dataset, it is written that the range of the attribute age is 18-58 .但是，在数据集的文档中，写了属性age的范围是18-58 。

pandas.cut will automatically bin according to the range of the dataset (which will be 18-55 ), which is wrong. pandas.cut会根据数据集的范围（将是18-55 ）自动pandas.cut ，这是错误的。

Is there any way I can specify the range to bin on in the pandas.cut method?有什么办法可以在pandas.cut方法中指定要pandas.cut的范围吗？ I looked into IntervalIndex tuples as bins, but that would mean that I generate the bins manually myself.我将IntervalIndex元组视为垃圾箱，但这意味着我自己手动生成垃圾箱。 I am looking for if pandas.cut has this functionality built-in.我正在寻找pandas.cut是否内置了此功能。

1 个解决方案

No, not directly.不，不是直接的。

However, you could pass np.linspace(18, 58, n_bins) to pd.cut .但是，您可以将np.linspace(18, 58, n_bins)传递给pd.cut 。 I'm not sure if you consider that "generating manually".我不确定您是否考虑“手动生成”。