Don't disable coalesce when joining on expressions

[mcrumiller]

Description

The documentation for join states the following for the coalesce parameter:

coalesce

Coalescing behavior (merging of join columns).

• None: -> join specific.
• True: -> Always coalesce join columns.
• False: -> Never coalesce join columns.

Note that joining on any other expressions than col will turn off coalescing.

I'm not sure why joining on other expressions disables coalescing. To get around this behavior, I find myself constantly using the following patterns:

df2 = df2.with_columns(
    col("name_1").operations().alias("tmp_name_1"),
    col("name_2").operations().alias("tmp_name_2"),
    col("name_3").operations().alias("tmp_name_3"),
)
df1.join(df2,
    left_on=["name_1", "name_2", "name_3"],
    right_on=["tmp_name_1", "tmp_name_2", "tmp_name_3"],
    how="left",
    coalesce=True,
).drop("tmp_name_1", "tmp_name_2", "tmp_name_3")

Instead, it would be preferable to be able to do:

df1.join(df2,
    left_on=["name_1", "name_2", "name_3"],
    right_on=[col("name_1").operations(), col("name_2").operations(), col("name_3").operations()],
    how="left",
    coalesce=True
)

[deanm0000]

One small tweak to your workaround

df2 = df2.with_columns(
    expr1.alias("name_1"),
    expr2.alias("name_2"),
    expr3.alias("name_3"),
)
df1.join(df2,
    on=["name_1", "name_2", "name_3"],
    how="left",
    coalesce=True,
)

I'm guessing that it was an implementation difficulty that made it the way it is rather than a planned decision. Maybe to do with handling aliases.

[mcrumiller]

@deanm0000 the problem is that name_1, name_2, and name_3 already exist in df2, but I need to do an operation on them, for example a .shift, so I cannot re-alias to the same name.

I updated my example above to make that a bit clearer.

[ritchie46]

It adds a lot of complexity and I don't think I am not sure it makes sense either.