如何将模型对象列表转换为pandas数据框? [英] How to convert list of model objects to pandas dataframe?

问题描述

我有一个此类的对象数组

I have an array of objects of this class

class CancerDataEntity(Model):

    age = columns.Text(primary_key=True)
    gender = columns.Text(primary_key=True)
    cancer = columns.Text(primary_key=True)
    deaths = columns.Integer()
    ...

打印后，数组看起来像这样

When printed, array looks like this

[CancerDataEntity(age=u'80-85+', gender=u'Female', cancer=u'All cancers (C00-97,B21)', deaths=15306), CancerDataEntity(...

我想将其转换为数据帧，以便我可以以更适合我的方式进行操作-进行汇总，计数，求和等. 我希望这个数据框看起来像这样:

I want to convert this to a data frame so I can play with it in a more suitable way to me - to aggregate, count, sum and similar. How I wish this data frame to look, would be something like this:

     age     gender     cancer     deaths
0    80-85+  Female     ...        15306
1    ...

是否有一种方法可以轻松地使用numpy/pandas来实现，而无需手动处理输入数组?

Is there a way to achieve this using numpy/pandas easily, without manually processing the input array?

推荐答案

导致所需结果的代码:

variables = arr[0].keys()
df = pd.DataFrame([[getattr(i,j) for j in variables] for i in arr], columns = variables)

感谢@Serbitar向我指出正确的方向.

Thanks to @Serbitar for pointing me to the right direction.

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