code: def test_infer_schema_with_names_pandas_instances(self):
      def func() -> (
          'pd.DataFrame["a" : np.float_, "b":str]'
      ):  # noqa: F405
          pass
  
      expected = StructType(
          [
              StructField("a", DoubleType()),
              StructField("b", StringType()),
          ]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.float64, np.unicode_])
      self.assertEqual(inferred.spark_type, expected)
  
      def func() -> "pd.DataFrame['a': float, 'b': int]":  # noqa: F405
          pass
  
      expected = StructType(
          [StructField("a", DoubleType()), StructField("b", LongType())]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.float64, np.int64])
      self.assertEqual(inferred.spark_type, expected)
  
      pdf = pd.DataFrame({"a": [1, 2, 3], "b": [3, 4, 5]})
  
      def func() -> pd.DataFrame[zip(pdf.columns, pdf.dtypes)]:
          pass
  
      expected = StructType(
          [StructField("a", LongType()), StructField("b", LongType())]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.int64, np.int64])
      self.assertEqual(inferred.spark_type, expected)
  
      pdf = pd.DataFrame({("x", "a"): [1, 2, 3], ("y", "b"): [3, 4, 5]})
  
      def func() -> pd.DataFrame[zip(pdf.columns, pdf.dtypes)]:
          pass
  
      expected = StructType(
          [
              StructField("(x, a)", LongType()),
              StructField("(y, b)", LongType()),
          ]
      )
      inferred = infer_return_type(func)
      self.assertEqual(inferred.dtypes, [np.int64, np.int64])
      self.assertEqual(inferred.spark_type, expected)
  
      pdf = pd.DataFrame(
          {"a": [1, 2, 3], "b": pd.Categorical(["a", "b", "c"])}
      )
  
      def func() -> pd.DataFrame[zip(pdf.columns, pdf.dtypes)]:
          pass
  
      expected = StructType(
          [StructField("a", LongType()), StructField("b", LongType())]
      )
      inferred = infer_return_type(func)
      self.assertEqual(
          inferred.dtypes,
          [np.int64, CategoricalDtype(categories=["a", "b", "c"])],
      )
      self.assertEqual(inferred.spark_type, expected)
  
imports: import sys
  import unittest
  import datetime
  import decimal
  from typing import List
  import pandas
  import pandas
  from pandas.api.types import CategoricalDtype
  import numpy
  from pyspark.loose_version import LooseVersion
  from pyspark.sql.types import ArrayType, BinaryType, BooleanType, FloatType, IntegerType, LongType, StringType, StructField, StructType, ByteType, ShortType, DateType, DecimalType, DoubleType, TimestampType
  from pyspark.pandas.typedef import as_spark_type, extension_dtypes_available, extension_float_dtypes_available, extension_object_dtypes_available, infer_return_type, pandas_on_spark_type
  from pyspark import pandas
label_desc: Use image node_id 4 for calling the TypeHintTestsMixin obj's underlying member method code with example usage: obj.test_infer_schema_with_names_pandas_instances() without return types