Python SDK read_parquet union_by_name fail after version 1.2.2

[duckdbtest.zip](https://github.com/user-attachments/files/24500181/duckdbtest.zip)

### What happens?

## Title
Regression in 1.3.0+: `union_by_name` fails with "Can't change source type (NULL) to target type (VARCHAR[])" when reading parquet files with mixed NULL/LIST types

## DuckDB Version
- **Working version**: 1.2.2
- **Broken versions**: 1.3.0, 1.3.1 (and later)

## Environment
- OS: Linux
- Python: 3.12.9
- pandas: (latest)

## Description

Starting with DuckDB 1.3.0, reading multiple parquet files with `union_by_name=True` fails when:
1. Some parquet files have a column stored as NULL type (because all values are null in that file)
2. Other parquet files have the same column properly typed as VARCHAR[] (array/list of strings)

This worked correctly in DuckDB 1.2.2 but now throws:
```
BinderException: Binder Error: Can't change source type ("NULL") to target type (VARCHAR[]), type conversion not allowed
```

### Expected Behavior
When `union_by_name=True` is set, DuckDB should merge schemas gracefully, treating NULL-typed columns as compatible with any target type (similar to how pandas handles this).

### Actual Behavior
DuckDB 1.3.0+ throws a `BinderException` and refuses to read the files, even though `union_by_name=True` is explicitly designed to handle schema variations across multiple files.

## Root Cause Analysis

Investigation shows:
- When a parquet file has ALL NULL values for a column, it's stored with NULL type (e.g., `INT32` with `NullType()` logical type)
- Other files with actual data store the same column as `BYTE_ARRAY` with `StringType()` or complex types like `ListType()`
- The error specifically mentions `VARCHAR[]` (array type) suggesting it happens with nested/complex types
- This regression appeared between versions 1.2.2 and 1.3.0

## How to Reproduce

attached files to test see [duckdbtest.zip](https://github.com/user-attachments/files/24500181/duckdbtest.zip)

```python
import duckdb
print(f"DuckDB version: {duckdb.__version__}")

# Fails with 1.3.0+
try:
result = duckdb.read_parquet(
"duckdb_bug_test_files/*.parquet",
union_by_name=True
).df()
print(f"SUCCESS: Read {len(result)} rows")
except Exception as e:
print(f"FAILED: {type(e).__name__}: {e}")
```

### To Reproduce

this is only in python SDK

### OS:

Linux x86

### DuckDB Version:

v1.2.2, v1.3.0 and later

### DuckDB Client:

Python

### Hardware:

_No response_

### Full Name:

Zack Dai

### Affiliation:

Zack Dai

### Did you include all relevant configuration (e.g., CPU architecture, Linux distribution) to reproduce the issue?

- [ ] Yes, I have

### Did you include all code required to reproduce the issue?

- [x] Yes, I have

### Did you include all relevant data sets for reproducing the issue?

Yes

Commencez par exécuter la reproduction Python avec l’archive duckdbtest.zip jointe sur DuckDB 1.2.2 et 1.3.0 ou version ultérieure, en utilisant read_parquet avec union_by_name=True. Suivez le chemin de fusion des schémas pour les colonnes NULL et VARCHAR[] et identifiez la régression. Le travail est considéré comme terminé lorsque les fichiers fournis se chargent correctement dans toutes les versions concernées, avec une couverture de régression pour ce cas.

Rédigé par le modèle d'indexation à partir du texte de l'issue.