python - 使用特定列对数据框进行子类化

Question

我正在尝试创建我自己的 Dataframe 类。我希望当我调用它时它有一些特定的列。所以我这样做:

from pandas import DataFrame

class MyClass(DataFrame):  

    def __init__(self):    
        super(MyClass, self).__init__(columns=['Class','Conditions']) 

但是，当我尝试向其附加数据时，

test = MyClass()
#test = MyClass(columns=['Class','Conditions'])

test.loc[2] = ['class2',[1, 2, 3]]

我收到错误:

File "C:\Miniconda3\lib\site-packages\pandas\core\indexing.py", line 189, in setitem self._setitem_with_indexer(indexer, value)

File "C:\Miniconda3\lib\site-packages\pandas\core\indexing.py", line 451, in _setitem_with_indexer self.obj._data = self.obj.append(value)._data

File "C:\Miniconda3\lib\site-packages\pandas\core\frame.py", line 6211, in append sort=sort)

File "C:\Miniconda3\lib\site-packages\pandas\core\reshape\concat.py", line 226, in concat return op.get_result()

File "C:\Miniconda3\lib\site-packages\pandas\core\reshape\concat.py", line 428, in get_result return (cons._from_axes(new_data, self.new_axes)

File "C:\Miniconda3\lib\site-packages\pandas\core\generic.py", line 356, in _from_axes return cls(data, **kwargs)

TypeError: init() takes 1 positional argument but 2 were given

我意识到，如果我不在 __init__ 中声明列并在创建类后分配它们，我就没有问题。

但是，我希望使用这些名称作为列来创建类。

非常感谢。

Answer 1

如果要使用构造函数进行初始化，则必须将参数传递给父级__init__

>>> class MyClass(DataFrame):                                                                                                                                              
        def __init__(self, *args, **kwargs):                                                                                                                                   
            kwargs['columns'] = ['Class', 'Conditions']                                                                                                                        
            super(MyClass, self).__init__(*args, **kwargs)                                                                                                                     

>>> md = MyClass({'Class': [1, 2, 3]})
>>> md
   Class Conditions
0      1        NaN
1      2        NaN
2      3        NaN