比较 pandas 列中的浮点数 [英] Comparing floats in a pandas column

问题描述

我有以下数据框:

       actual_credit    min_required_credit
   0   0.3              0.4
   1   0.5              0.2
   2   0.4              0.4
   3   0.2              0.3

我需要添加一列来指示实际信用> = min_required_credit的位置.结果将是:

I need to add a column indicating where actual_credit >= min_required_credit. The result would be:

       actual_credit    min_required_credit   result
   0   0.3              0.4                   False
   1   0.5              0.2                   True
   2   0.4              0.4                   True
   3   0.1              0.3                   False

我正在执行以下操作:

df['result'] = abs(df['actual_credit']) >= abs(df['min_required_credit'])

但是，第三行(0.4和0.4)始终导致False.在各个地方研究了此问题后，包括:

However the 3rd row (0.4 and 0.4) is constantly resulting in False. After researching this issue at various places including: What is the best way to compare floats for almost-equality in Python? I still can't get this to work. Whenever the two columns have an identical value, the result is False which is not correct.

我正在使用python 3.3

I am using python 3.3

推荐答案

由于不精确的浮点比较，您可以or与

Due to imprecise float comparison you can or your comparison with np.isclose, isclose takes a relative and absolute tolerance param so the following should work:

df['result'] = df['actual_credit'].ge(df['min_required_credit']) | np.isclose(df['actual_credit'], df['min_required_credit'])

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