pandas.DataFrame.swaplevel#

DataFrame.swaplevel(i=-2, j=-1, axis=0)[source] #

Swap levels i and j in a MultiIndex.

Default is to swap the two innermost levels of the index.

Parameters:

i, jint or str

Levels of the indices to be swapped. Can pass level name as string.

axis{0 or ‘index’, 1 or ‘columns’}, default 0

The axis to swap levels on. 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise.

Returns:

DataFrame

DataFrame with levels swapped in MultiIndex.

Examples

>>> df = pd.DataFrame(
...  {"Grade": ["A", "B", "A", "C"]},
...  index=[
...  ["Final exam", "Final exam", "Coursework", "Coursework"],
...  ["History", "Geography", "History", "Geography"],
...  ["January", "February", "March", "April"],
...  ],
... )
>>> df
 Grade
Final exam History January A
 Geography February B
Coursework History March A
 Geography April C

In the following example, we will swap the levels of the indices. Here, we will swap the levels column-wise, but levels can be swapped row-wise in a similar manner. Note that column-wise is the default behaviour. By not supplying any arguments for i and j, we swap the last and second to last indices.

>>> df.swaplevel()
 Grade
Final exam January History A
 February Geography B
Coursework March History A
 April Geography C

By supplying one argument, we can choose which index to swap the last index with. We can for example swap the first index with the last one as follows.

>>> df.swaplevel(0)
 Grade
January History Final exam A
February Geography Final exam B
March History Coursework A
April Geography Coursework C

We can also define explicitly which indices we want to swap by supplying values for both i and j. Here, we for example swap the first and second indices.

>>> df.swaplevel(0, 1)
 Grade
History Final exam January A
Geography Final exam February B
History Coursework March A
Geography Coursework April C