Selecting columns from LazyFrame after join_where fails with DuplicateError

[Matt711]

Checks

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of Polars.

Reproducible example

With polars==1.20.0

In [1]: import polars as pl

In [2]: left=pl.LazyFrame(
   ...:         {
   ...:             "a": [1, 2, 3, 1, None],
   ...:             "b": [1, 2, 3, 4, 5],
   ...:             "c": [2, 3, 4, 5, 6],
   ...:         }
   ...:     )

In [3]: right=pl.LazyFrame(
   ...:         {
   ...:             "a": [1, 4, 3, 7, None, None, 1],
   ...:             "c": [2, 3, 4, 5, 6, 7, 8],
   ...:             "d": [6, None, 7, 8, -1, 2, 4],
   ...:         }
   ...:     )

In [4]: q = left.join_where(right, *[pl.col("b") * 2 <= pl.col("a_right"), pl.col("a") < pl.col("c_right")])

In [5]: q.select(pl.len()).collect()
DuplicateError: the name 'a' is duplicate

Log output

join parallel: true
IEJOIN join dataframes finished
---------------------------------------------------------------------------
DuplicateError                            Traceback (most recent call last)
Cell In[5], line 1
----> 1 q.select(pl.len()).collect()

File ~/.conda/envs/rapids/lib/python3.12/site-packages/polars/lazyframe/frame.py:2056, in LazyFrame.collect(self, type_coercion, _type_check, predicate_pushdown, projection_pushdown, simplify_expression, slice_pushdown, comm_subplan_elim, comm_subexpr_elim, cluster_with_columns, collapse_joins, no_optimization, streaming, engine, background, _check_order, _eager, **_kwargs)
   2054 # Only for testing purposes
   2055 callback = _kwargs.get("post_opt_callback", callback)
-> 2056 return wrap_df(ldf.collect(callback))

DuplicateError: the name 'a' is duplicate

It's possible that multiple expressions are returning the same default column name. If this is the case, try renaming the columns with `.alias("new_name")` to avoid duplicate column names.

Issue description

The difference might be due to this PR: #20223

Expected behavior

With polars==1.17.1

In [1]: import polars as pl

In [2]: left=pl.LazyFrame(
   ...:         {
   ...:             "a": [1, 2, 3, 1, None],
   ...:             "b": [1, 2, 3, 4, 5],
   ...:             "c": [2, 3, 4, 5, 6],
   ...:         }
   ...:     )

In [3]: right=pl.LazyFrame(
   ...:         {
   ...:             "a": [1, 4, 3, 7, None, None, 1],
   ...:             "c": [2, 3, 4, 5, 6, 7, 8],
   ...:             "d": [6, None, 7, 8, -1, 2, 4],
   ...:         }
   ...:     )

In [4]: q = left.join_where(right, *[pl.col("b") * 2 <= pl.col("a_right"), pl.col("a") < pl.col("c_right")])

In [5]: q.select(pl.len()).collect()
join parallel: true
IEJOIN join dataframes finished
Out[5]: 
shape: (1, 1)
┌─────┐
│ len │
│ --- │
│ u32 │
╞═════╡
│ 6   │
└─────┘

Installed versions

--------Version info---------
Polars:              1.20.0
Index type:          UInt32
Platform:            Linux-5.4.0-182-generic-x86_64-with-glibc2.35
Python:              3.12.8 | packaged by conda-forge | (main, Dec  5 2024, 14:24:40) [GCC 13.3.0]
LTS CPU:             False

----Optional dependencies----
Azure CLI            <not installed>
adbc_driver_manager  <not installed>
altair               <not installed>
azure.identity       <not installed>
boto3                1.36.1
cloudpickle          3.1.1
connectorx           <not installed>
deltalake            <not installed>
fastexcel            0.12.1
fsspec               2024.12.0
gevent               <not installed>
google.auth          <not installed>
great_tables         <not installed>
matplotlib           <not installed>
nest_asyncio         1.6.0
numpy                2.0.2
openpyxl             3.1.5
pandas               2.2.3
pyarrow              18.1.0
pydantic             <not installed>
pyiceberg            <not installed>
sqlalchemy           2.0.37
torch                2.5.1.post303
xlsx2csv             <not installed>
xlsxwriter           <not installed>