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

Bắt đầu bằng cách chạy bản tái hiện bằng Python với duckdbtest.zip đính kèm trên DuckDB 1.2.2 và 1.3.0 trở lên, sử dụng read_parquet với union_by_name=True. Theo dõi đường dẫn hợp nhất schema đối với các cột NULL và VARCHAR[] và xác định regression. Công việc được xem là hoàn tất khi các tệp được cung cấp tải thành công trên tất cả các phiên bản bị ảnh hưởng, với regression coverage cho trường hợp này.

Do mô hình lập chỉ mục viết ra từ nội dung của issue.