code: def test_drop(self):
      pdf = pd.DataFrame({"x": [10, 20, 15, 30, 45]})
      psdf = ps.from_pandas(pdf)
      pser, psser = pdf.x, psdf.x
  
      self.assert_eq(psser.drop(1), pser.drop(1))
      self.assert_eq(psser.drop([1, 4]), pser.drop([1, 4]))
      self.assert_eq(psser.drop(columns=1), pser.drop(columns=1))
      self.assert_eq(
          psser.drop(columns=[1, 4]), pser.drop(columns=[1, 4])
      )
  
      msg = "Need to specify at least one of 'labels', 'index' or 'columns'"
      with self.assertRaisesRegex(ValueError, msg):
          psser.drop()
      self.assertRaises(KeyError, lambda: psser.drop((0, 1)))
  
      psser.drop([2, 3], inplace=True)
      pser.drop([2, 3], inplace=True)
      self.assert_eq(psser, pser)
      self.assert_eq(psdf, pdf)
  
      n_pser, n_psser = pser + 1, psser + 1
      n_psser.drop([1, 4], inplace=True)
      n_pser.drop([1, 4], inplace=True)
      self.assert_eq(n_psser, n_pser)
      self.assert_eq(psser, pser)
  
      # For MultiIndex
      midx = pd.MultiIndex(
          [["lama", "cow", "falcon"], ["speed", "weight", "length"]],
          [[0, 0, 0, 1, 1, 1, 2, 2, 2], [0, 1, 2, 0, 1, 2, 0, 1, 2]],
      )
  
      pdf = pd.DataFrame(
          {"x": [45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3]}, index=midx
      )
      psdf = ps.from_pandas(pdf)
      psser, pser = psdf.x, pdf.x
  
      self.assert_eq(psser.drop("lama"), pser.drop("lama"))
      self.assert_eq(
          psser.drop(labels="weight", level=1),
          pser.drop(labels="weight", level=1),
      )
      self.assert_eq(
          psser.drop(("lama", "weight")), pser.drop(("lama", "weight"))
      )
      self.assert_eq(
          psser.drop([("lama", "speed"), ("falcon", "weight")]),
          pser.drop([("lama", "speed"), ("falcon", "weight")]),
      )
      self.assert_eq(
          psser.drop({"lama": "speed"}), pser.drop({"lama": "speed"})
      )
  
      msg = "'level' should be less than the number of indexes"
      with self.assertRaisesRegex(ValueError, msg):
          psser.drop(labels="weight", level=2)
  
      msg = (
          "If the given index is a list, it "
          "should only contains names as all tuples or all non tuples "
          "that contain index names"
      )
      with self.assertRaisesRegex(ValueError, msg):
          psser.drop(["lama", ["cow", "falcon"]])
  
      msg = "Cannot specify both 'labels' and 'index'/'columns'"
      with self.assertRaisesRegex(ValueError, msg):
          psser.drop("lama", index="cow")
  
      with self.assertRaisesRegex(ValueError, msg):
          psser.drop("lama", columns="cow")
  
      msg = r"'Key length \(2\) exceeds index depth \(3\)'"
      with self.assertRaisesRegex(KeyError, msg):
          psser.drop(("lama", "speed", "x"))
  
      psser.drop({"lama": "speed"}, inplace=True)
      pser.drop({"lama": "speed"}, inplace=True)
      self.assert_eq(psser, pser)
      self.assert_eq(psdf, pdf)
  
imports: import unittest
  from itertools import product
  import numpy
  import pandas
  from pyspark import pandas
  from pyspark.errors import PySparkValueError
  from pyspark.testing.pandasutils import ComparisonTestBase
  from pyspark.testing.sqlutils import SQLTestUtils
label_desc: Use image node_id 9 for calling the SeriesComputeMixin obj's underlying member method code with example usage: obj.test_drop() without return types