Truth.swaplevel

Truth.swaplevel#

missionbio.demultiplex.dna.truth.Truth.swaplevel

Truth.swaplevel(i: Union[str, int] = -2, j: Union[str, int] = -1, axis: Union[str, int] = 0) → DataFrame#

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

< Class Truth

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