Option to suppress automatic conversion of tuples to MultiIndex

Right now we have:

>>> pd.DataFrame({(1,2):pd.Series([2.3])}).columns
MultiIndex(levels=[[1], [2]],                     
           labels=[[0], [0]])                     
>>> pd.Index([(1,2)])
MultiIndex(levels=[[1], [2]],
           labels=[[0], [0]])

Could we have an option to suppress this behavior? One problem this causes is that the .rename method is not uniform and does not work if a tuple is silently converted:

>>> pd.DataFrame({(1,2):pd.Series([2.3])}).rename(columns={(1,2):(1,3)})
     1                                                                  
     2                                                                  
0  2.3                                                                  

To see why such behavior is problematic consider the following unintuitive example:

>>> a = ('a', 1)

>>> b = ('b', 2)

>>> pd.DataFrame({a:pd.Series([2,3])})
   a
   1
0  2
1  3

>>> pd.DataFrame({a:pd.Series([2,3])}).rename(columns={a:b})
   a
   1
0  2
1  3

[htzh]

Thanks to all for the help. I think I will try to grok MultiIndex better and more effectively incorporate it into the processing pipeline sooner. I also realized that one way to achieve what I wanted is to first convert names of rows as a data column and change the names in the data column. Pandas offers convenient ways to then use the changed column as Index or MultiIndex.

@jreback I read the #4160 thread but it is not completely clear to me what the proposed API is. Is the proposal to make the following statement work for MultiIndex:

df.rename(columns={('abspx','red) : ('foo','orange')})

presumably moving the particular column from one part of the hierarchy to another? If that is the proposal that is also what I requested earlier: “rename method (for DataFrame or Series) accepts tuple as specifying MultiIndex instead of tuple index just like in operator does.”

I am not yet familiar with pandas source but I will keep that in mind.

[htzh]

I accept that tuple is not desirable. My problem is that during data cleaning phase I need to rename index (column or row) at a few places. However the conversion of tuple to MultiIndex is not consistent for row index:

>>> pd.DataFrame({'a':pd.Series([2, 3], index=[(1,1), (2,2)])})
        a
(1, 1)  2
(2, 2)  3

And as rename semantics is not uniform between Index and MultiIndex, it would be nice to have consistent behavior here:

• tuple row index converts to MultiIndex
• rename method (for DataFrame or Series) accepts tuple as specifying MultiIndex instead of tuple index just like in operator does.