Suppose I have the following DataFrame:

arrays = [[1, 1, 2, 2], ["red", "blue", "red", "blue"]]
ix = pd.MultiIndex.from_arrays(arrays, names=("number", "color"))
df = pd.DataFrame([[10, 20, 30, 40], [50, 60, 70, 80]], columns=ix)
df

I would like to flatten the MultiIndex column like that:

df.columns = [str(x[0])+"_"+str(x[1]) for x in df.columns]
df

But I would like to do it in a pipe.

For instance, supposing the function rename_columns would exist (it doesn't), it would look like:

df.rename_columns(lambda x: str(x[0])+"_"+str(x[1]))

Said otherwise, I would like to write that rename_columns function.

How can I achieve this?

EDIT: The rename function doesn't work:

df.rename(lambda x: str(x[0])+"_"+str(x[1]))

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[28], line 1
----> 1 df.rename(lambda x: str(x[0])+"_"+str(x[1]))

File .venv\Lib\site-packages\pandas\core\frame.py:6471, in DataFrame.rename(self, mapper, index, columns, axis, copy, inplace, level, errors)
   6352 """
   6353 Rename columns or index labels.
   6354 
   (...)   6468 4  3  6
   6469 """
   6470 self._check_copy_deprecation(copy)
-> 6471 return super()._rename(
   6472     mapper=mapper,
   6473     index=index,
   6474     columns=columns,
   6475     axis=axis,
   6476     inplace=inplace,
   6477     level=level,
   6478     errors=errors,
   6479 )

File .venv\Lib\site-packages\pandas\core\generic.py:1065, in NDFrame._rename(self, mapper, index, columns, axis, inplace, level, errors)
   1058             missing_labels = [
   1059                 label
   1060                 for index, label in enumerate(replacements)
   1061                 if indexer[index] == -1
   1062             ]
   1063             raise KeyError(f"{missing_labels} not found in axis")
-> 1065     new_index = ax._transform_index(f, level=level)
   1066     result._set_axis_nocheck(new_index, axis=axis_no, inplace=True)
   1068 if inplace:

File .venv\Lib\site-packages\pandas\core\indexes\base.py:6672, in Index._transform_index(self, func, level)
   6670     return type(self).from_arrays(values)
   6671 else:
-> 6672     items = [func(x) for x in self]
   6673     return Index(items, name=self.name, tupleize_cols=False)

Cell In[28], line 1
----> 1 df.rename(lambda x: str(x[0])+"_"+str(x[1]))

TypeError: 'int' object is not subscriptable