[SPARK-40376][PYTHON] Avoid Numpy deprecation warning

### What changes were proposed in this pull request?

Use `bool` instead of `np.bool` as `np.bool` will be deprecated (see: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations)

Using `np.bool` generates this warning:

```
UserWarning: toPandas attempted Arrow optimization because 'spark.sql.execution.arrow.pyspark.enabled' is set to true, but has reached the error below and can not continue. Note that 'spark.sql.execution.arrow.pyspark.fallback.enabled' does not have an effect on failures in the middle of computation.
3070E                     `np.bool` is a deprecated alias for the builtin `bool`. To silence this warning, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here.
3071E                   Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
```

### Why are the changes needed?
Deprecation soon: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations.

### Does this PR introduce _any_ user-facing change?
The warning will be suppressed

### How was this patch tested?
Existing tests should suffice.

Closes #37817 from ELHoussineT/patch-1.

Authored-by: ELHoussineT <[email protected]>
Signed-off-by: Sean Owen <[email protected]>

Author: ELHoussineT

python/pyspark/sql/pandas/conversion.py

@@ -295,7 +295,7 @@ def _to_corrected_pandas_type(dt: DataType) -> Optional[Type]:
         elif type(dt) == DoubleType:
             return np.float64
         elif type(dt) == BooleanType:
-            return np.bool  # type: ignore[attr-defined]
+            return bool
         elif type(dt) == TimestampType:
             return np.datetime64
         elif type(dt) == TimestampNTZType: