[Python] How to swap column values on conditions in python polars?

I have a data frame as below:

df = pl.DataFrame({'last_name':[None,'mallesh','bhavik'],
'first_name':['a','b','c'],
'middle_name_or_initial':['aa','bb','cc']})


shape: (3, 3)
┌───────────┬────────────┬────────────────────────┐
│ last_name ┆ first_name ┆ middle_name_or_initial │
│ --- ┆ --- ┆ --- │
│ str ┆ str ┆ str │
╞═══════════╪════════════╪════════════════════════╡
│ null ┆ a ┆ aa │
│ mallesh ┆ b ┆ bb │
│ bhavik ┆ c ┆ cc │
└───────────┴────────────┴────────────────────────┘


Here I would like to find an observation which has First and Middle Name not NULL and Last Name is Null.

In this case last_name should take the value from first_name, first_name should take the value from middle_name, and middle_name should be NULL.

expected output will be:

shape: (3, 3)
┌───────────┬────────────┬────────────────────────┐
│ last_name ┆ first_name ┆ middle_name_or_initial │
│ --- ┆ --- ┆ --- │
│ str ┆ str ┆ str │
╞═══════════╪════════════╪════════════════════════╡
│ a ┆ aa ┆ null │
│ mallesh ┆ b ┆ bb │
│ bhavik ┆ c ┆ cc │
└───────────┴────────────┴────────────────────────┘


I'm trying with this command:

df.with_columns(
pl.when((pl.col('first_name').is_not_null()) & (pl.col('middle_name_or_initial').is_not_null()) & (pl.col('last_name').is_null()))
.then(pl.col('first_name').alias('last_name')).otherwise(pl.col('last_name').alias('first_name')),
pl.when((pl.col('first_name').is_not_null()) & (pl.col('middle_name_or_initial').is_not_null()) & (pl.col('last_name').is_null()))
.then(pl.col('middle_name_or_initial').alias('first_name')).alias('middle_name_or_initial')
)


But it is not producing the expected output.

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