pandas 用不同的列连接数据帧:AttributeError:'NoneType'对象没有属性'is_extension' [英] Pandas concat dataframes with different columns: AttributeError: 'NoneType' object has no attribute 'is_extension'

问题描述

我正在尝试连接两个数据框，它们沿0轴具有不同的列名.我在这里

I am trying to concatenate two dataframes which have different column names along the 0 axis. I found a similar question here How to use join_axes in the column-wise axis concatenation using pandas DataFrame? however this solution does not work for me since the column-names of my two dataframes are not the same. Since my original data is too large to post here the following example should illustrates what I am trying to do:

df1 = pd.DataFrame(np.random.randint(0,100,size=(1, 4)), columns=list('ABCD'))
df2 = pd.DataFrame(np.random.randint(0,100,size=(1, 4)), columns=list('EFGH'))

#df1
    A   B   C   D
0   26  39  7   44

#df2
    E   F   G   H
0   12  44  26  64

pd.concat([df1,df2],axis=0).reset_index(drop=True)
# desired output looks like this
A   B   C   D   E   F   G   H
0   26.0    39.0    7.0 44.0    NaN NaN NaN NaN
1   NaN NaN NaN NaN 12.0    44.0    26.0    64.0

上面的代码运行完美.但是，一旦我使用上面完全相同的语法为df1和df2输入了自己的数据帧，就会收到错误消息.

The above code works perfectly. However, once I input my own dataframes for df1 and df2, using the exact same syntax above, I get an error.

# my real dfs are called data1 & data2, I tried setting ignore_index=True and ignore_index=False
pd.concat([data1, data2],axis=0, ignore_index=True)

导致以下错误:

错误:

 ---------------------------------------------------------------------------
    AttributeError                            Traceback (most recent call last)
    <ipython-input-194-dbee1fd0bdea> in <module>
    ----> 1 pd.concat([data1, data2],axis=0, ignore_index=True)

    ~\AppData\Local\Continuum\anaconda3\envs\tensorflow-gpu\lib\site-packages\pandas\core\reshape\concat.py in concat(objs, axis, join, join_axes, ignore_index, keys, levels, names, verify_integrity, sort, copy)
        224                        verify_integrity=verify_integrity,
        225                        copy=copy, sort=sort)
    --> 226     return op.get_result()
        227 
        228 

    ~\AppData\Local\Continuum\anaconda3\envs\tensorflow-gpu\lib\site-packages\pandas\core\reshape\concat.py in get_result(self)
        421             new_data = concatenate_block_managers(
        422                 mgrs_indexers, self.new_axes, concat_axis=self.axis,
    --> 423                 copy=self.copy)
        424             if not self.copy:
        425                 new_data._consolidate_inplace()

    ~\AppData\Local\Continuum\anaconda3\envs\tensorflow-gpu\lib\site-packages\pandas\core\internals.py in concatenate_block_managers(mgrs_indexers, axes, concat_axis, copy)
       5414                 values = values.view()
       5415             b = b.make_block_same_class(values, placement=placement)
    -> 5416         elif is_uniform_join_units(join_units):
       5417             b = join_units[0].block.concat_same_type(
       5418                 [ju.block for ju in join_units], placement=placement)

    ~\AppData\Local\Continuum\anaconda3\envs\tensorflow-gpu\lib\site-packages\pandas\core\internals.py in is_uniform_join_units(join_units)
       5438         # no blocks that would get missing values (can lead to type upcasts)
       5439         # unless we're an extension dtype.
    -> 5440         all(not ju.is_na or ju.block.is_extension for ju in join_units) and
       5441         # no blocks with indexers (as then the dimensions do not fit)
       5442         all(not ju.indexers for ju in join_units) and

    ~\AppData\Local\Continuum\anaconda3\envs\tensorflow-gpu\lib\site-packages\pandas\core\internals.py in <genexpr>(.0)
       5438         # no blocks that would get missing values (can lead to type upcasts)
       5439         # unless we're an extension dtype.
    -> 5440         all(not ju.is_na or ju.block.is_extension for ju in join_units) and
       5441         # no blocks with indexers (as then the dimensions do not fit)
       5442         all(not ju.indexers for ju in join_units) and

    AttributeError: 'NoneType' object has no attribute 'is_extension'

我不太明白此错误消息试图告诉我什么.我一直在尝试在两个数据帧上都使用fillna，这样就不再有"NoneType"了:

I do not quite understand what this error message is trying to tell me. I've been trying to use fillna on both dataframes such that there should be no 'NoneType' anymore:

data2 = data2.fillna(999)
data1 = data1.fillna(999)

但是，我仍然收到相同的错误消息.

However, I still get the same error message.

我正在使用的两个数据帧非常大，因此很遗憾，我无法在此处发布整个示例.我的两个数据帧的内容只是整数，浮点数和字符串，因此在这里没有什么花哨的事情会引起错误.是否知道可能导致此错误的原因或我可以检查以缩小问题范围的任何想法?

The two dataframes I am using are quite large, so I cant unfortunately post the entire example here. The content of my two dataframes are just integers, floats and strings so nothing fancy going on here that would strike a possible cause of error. Any idea on what might cause this error or what I could check to narrow down the problem?

非常感谢！

推荐答案

原来的问题只是我的一个数据框中的重复的列名 ...摆脱了解决问题的那些重复项.上面的代码现在可以完美地工作了.

Turns out the problem were just duplicate column names in one of my dataframes...Getting rid of those duplicates solved to problem. Above code now works flawlessly.

这篇关于 pandas 用不同的列连接数据帧:AttributeError:'NoneType'对象没有属性'is_extension'的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！