code: def test_filter(self):
      pser = pd.Series([0, 1, 2], index=["one", "two", "three"])
      psser = ps.from_pandas(pser)
  
      self.assert_eq(
          pser.filter(items=["one", "three"]),
          psser.filter(items=["one", "three"]),
      )
      self.assert_eq(pser.filter(regex="e$"), psser.filter(regex="e$"))
      self.assert_eq(pser.filter(like="hre"), psser.filter(like="hre"))
  
      with self.assertRaisesRegex(
          ValueError, "Series does not support columns axis."
      ):
          psser.filter(like="hre", axis=1)
  
      # for MultiIndex
      midx = pd.MultiIndex.from_tuples(
          [("one", "x"), ("two", "y"), ("three", "z")]
      )
      pser = pd.Series([0, 1, 2], index=midx)
      psser = ps.from_pandas(pser)
  
      self.assert_eq(
          pser.filter(items=[("one", "x"), ("three", "z")]),
          psser.filter(items=[("one", "x"), ("three", "z")]),
      )
  
      with self.assertRaisesRegex(TypeError, "Unsupported type list"):
          psser.filter(items=[["one", "x"], ("three", "z")])
  
      with self.assertRaisesRegex(
          ValueError, "The item should not be empty."
      ):
          psser.filter(items=[(), ("three", "z")])
  
imports: import unittest
  from collections import defaultdict
  import inspect
  from datetime import datetime, timedelta
  import numpy
  import pandas
  from pyspark.ml.linalg import SparseVector
  from pyspark import pandas
  from pyspark.testing.pandasutils import PandasOnSparkTestCase, SPARK_CONF_ARROW_ENABLED
  from pyspark.testing.sqlutils import SQLTestUtils
  from pyspark.pandas.exceptions import PandasNotImplementedError
  from pyspark.pandas.missing.series import MissingPandasLikeSeries
  from pyspark.pandas.typedef.typehints import extension_object_dtypes_available
label_desc: Use image node_id 37 for calling the SeriesTestsMixin obj's underlying member method code with example usage: obj.test_filter() without return types