问题描述
我需要创建一个包含DataFrames
列的DataFrame
.列中的DataFrames
具有不同的大小,并且出现了StopIteration
异常.当DataFrames
的大小相同时,不会发生这种情况.我知道Panel
更适合此情况,但是在这种情况下,我需要DataFrame
.
I need to create a DataFrame
that contains columns of DataFrames
. The DataFrames
that go in the column have different sizes and I am getting a StopIteration
exception. This doesn't happen, when the DataFrames
are of the same size. I know a Panel
is more suitable for this, but I need a DataFrame
in this case.
a=pd.DataFrame({'cat1':['one','two','three'],'cat2':['four','five','six']})
b=pd.DataFrame({'cat1':['ten','eleven'],'cat2':['twelve','thirteen']})
pd.DataFrame({'col1':{'row1':a,'row2':b}})
如果我分别从"cat1","cat2"中删除三个"和六个"项目,则此方法工作正常.知道我该如何实现吗?
If I remove the 'three' and 'six' items from 'cat1', 'cat2' respectively, then this works fine. Any idea how I can achieve this?
推荐答案
这不是一个好主意,您会失去所有效率,因为事情被视为object
dtype且操作将非常缓慢(因为操作无法通过c级基本类型,例如float/int).更好的方法是使用多级索引,该索引可以轻松包含我认为想要的内容
this is not a good idea, you lose all efficiency because things are treated as object
dtype and operations will be quite slow (as operations cannot be done via c-level base types, like float/int). Better is to use a multi-level index, which can easily encompass what I think you want
In [20]: a
Out[20]:
cat1 cat2
0 one four
1 two five
2 three six
In [21]: b
Out[21]:
cat1 cat2
0 ten twelve
1 eleven thirteen
In [22]: pd.concat([ a, b ], keys={ 'row1' : a, 'row2' : b })
Out[22]:
cat1 cat2
row1 0 one four
1 two five
2 three six
row2 0 ten twelve
1 eleven thirteen
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