pandas.Series.swaplevel¶

Series.swaplevel(i=- 2, j=- 1, copy=True)[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.
copybool, default True: Whether to copy underlying data.

Returns

Series: Series with levels swapped in MultiIndex.

Examples

>>> s = pd.Series(
...     ["A", "B", "A", "C"],
...     index=[
...         ["Final exam", "Final exam", "Coursework", "Coursework"],
...         ["History", "Geography", "History", "Geography"],
...         ["January", "February", "March", "April"],
...     ],
... )
>>> s
Final exam  History     January      A
            Geography   February     B
Coursework  History     March        A
            Geography   April        C
dtype: object

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.

>>> s.swaplevel()
Final exam  January     History         A
            February    Geography       B
Coursework  March       History         A
            April       Geography       C
dtype: object

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.

>>> s.swaplevel(0)
January     History     Final exam      A
February    Geography   Final exam      B
March       History     Coursework      A
April       Geography   Coursework      C
dtype: object

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.

>>> s.swaplevel(0, 1)
History     Final exam  January         A
Geography   Final exam  February        B
History     Coursework  March           A
Geography   Coursework  April           C
dtype: object

pandas.Series.swapaxes

pandas.Series.tail