[BUGFIX] Fix misleading result format docs for ExpectColumnValuesToBeOfType (#11076)

[creazyfrog]

Summary

Fixes #11076

The docstring Code Examples for ExpectColumnValuesToBeOfType showed the full Column Map result format (element_count, unexpected_count, partial_unexpected_list, etc.) for all backends. In practice this format is only returned when Pandas is used with a column whose dtype is object (row-level type inspection). For all other backends — SQL (Databricks, Snowflake, SQL Server, PostgreSQL, Trino), Spark, and Pandas with non-object dtypes — the expectation validates the column's schema-level data type and returns only {"observed_value": "<type_name>"}, making the documented examples actively misleading.

Users on Databricks or Spark opened issue #11076 because they expected the full map format based on the docs.

Root Cause

_validate_pandas (non-object path), _validate_sqlalchemy, and _validate_spark perform a schema-level aggregate check — there are no "unexpected rows" to enumerate, so the full Column Map output (element_count, unexpected_count, partial_unexpected_list, etc.) is fundamentally unavailable. The only meaningful result field is observed_value (the actual column type). The Code Examples in the docstring were copied from a different context (the Pandas row-level map path) without being adjusted for the aggregate paths.

Changes

great_expectations/expectations/core/expect_column_values_to_be_of_type.py

• Replaced the two misleading Code Examples with a clear Result Format section that documents both shapes and explains exactly when each applies:
  • SQL / Spark / Pandas non-object dtype → {"observed_value": "<type>"}
  • Pandas with object dtype → full Column Map format (element_count, unexpected_count, etc.)
• Updated the Code Examples to show the observed_value format, which is what the vast majority of users actually see.

tests/expectations/core/test_expect_column_values_to_be_of_type.py

• Added test_expect_column_values_to_be_of_type_result_contains_observed_value_for_pandas — a unit test that asserts observed_value is present and element_count is absent for a Pandas non-object column, preventing a future regression where the aggregate path accidentally returns the map format.

Test plan

• test_expect_column_values_to_be_of_type_result_contains_observed_value_for_pandas (new unit test)
• Verified manually on Pandas, SQLite, and mocked Databricks dialect that result contains only observed_value for all aggregate-mode paths