[BUGFIX] ExpectColumnValuesToBeOfType returns full map-format result for all backends

[EshwarCVS]

Summary

Fixes #11076 — ExpectColumnValuesToBeOfType was returning only
{"observed_value": <type>} for non-object Pandas dtypes, SQLAlchemy,
and Spark backends instead of the standard ColumnMapExpectation result
structure documented in the expectation.

Also confirms #11026 (accented characters in row_condition strings) is
already resolved via alphas8bit in legacy_row_conditions.py.

Changes

• expect_column_values_to_be_of_type.py

  • Added table.row_count and column_values.nonnull.unexpected_count
    to get_validation_dependencies for all backends so missing/null
    stats are always available.
  • Added _build_map_result() helper that wraps aggregate type-check
    results through _format_map_output, computing nonnull_count from
    the null metric and preserving observed_value.
  • Updated _validate() to route non-map paths through _build_map_result.

• test_expect_column_values_to_be_of_type.py

  • Added tests verifying the full result schema on success, failure, and
    columns containing nulls.

Before / After

Before:

{ "success": false, "result": { "observed_value": "StringType" } }

After:

{
  "success": false,
  "result": {
    "element_count": 5,
    "unexpected_count": 4,
    "unexpected_percent": 100.0,
    "partial_unexpected_list": [],
    "missing_count": 1,
    "missing_percent": 20.0,
    "unexpected_percent_total": 80.0,
    "unexpected_percent_nonmissing": 100.0,
    "observed_value": "StringType"
  }
}

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[EshwarCVS]

Didn't see #11855
Similar changes in this PR can be ignored

[joshua-stauffer]

thanks for the PR @EshwarCVS . This expectation is unusual in that the Pandas implementation behaves as a row level check, while the Spark and SQL implementations behave as a schema level check. We'll address the gap, but haven't settled on a solution yet. I'll leave this open, but will hold off reviewing for the time being.

[github-actions]

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