text: import re
  
  import numpy as np
  import pytest
  
  from pandas import DataFrame, Series
  import pandas.util.testing as tm
  
  
  @pytest.mark.parametrize("subset", ["a", ["a"], ["a", "B"]])
  def test_duplicated_with_misspelled_column_name(subset):
      # GH 19730
      df = DataFrame({"A": [0, 0, 1], "B": [0, 0, 1], "C": [0, 0, 1]})
      msg = re.escape("Index(['a'], dtype='object')")
  
      with pytest.raises(KeyError, match=msg):
          df.duplicated(subset)
  
      with pytest.raises(KeyError, match=msg):
          df.drop_duplicates(subset)
  
  
  @pytest.mark.slow
  def test_duplicated_do_not_fail_on_wide_dataframes():
      # gh-21524
      # Given the wide dataframe with a lot of columns
      # with different (important!) values
      data = {
          "col_{0:02d}".format(i): np.random.randint(0, 1000, 30000) for i in range(100)
      }
      df = DataFrame(data).T
      result = df.duplicated()
  
      # Then duplicates produce the bool Series as a result and don't fail during
      # calculation. Actual values doesn't matter here, though usually it's all
      # False in this case
      assert isinstance(result, Series)
      assert result.dtype == np.bool
  
  
  @pytest.mark.parametrize(
      "keep, expected",
      [
          ("first", Series([False, False, True, False, True])),
          ("last", Series([True, True, False, False, False])),
          (False, Series([True, True, True, False, True])),
      ],
  )
  def test_duplicated_keep(keep, expected):
      df = DataFrame({"A": [0, 1, 1, 2, 0], "B": ["a", "b", "b", "c", "a"]})
  
      result = df.duplicated(keep=keep)
      tm.assert_series_equal(result, expected)
  
  
  @pytest.mark.xfail(reason="GH#21720; nan/None falsely considered equal")
  @pytest.mark.parametrize(
      "keep, expected",
      [
          ("first", Series([False, False, True, False, True])),
          ("last", Series([True, True, False, False, False])),
          (False, Series([True, True, True, False, True])),
      ],
  )
  def test_duplicated_nan_none(keep, expected):
      df = DataFrame({"C": [np.nan, 3, 3, None, np.nan]}, dtype=object)
  
      result = df.duplicated(keep=keep)
      tm.assert_series_equal(result, expected)
  
  
  @pytest.mark.parametrize("keep", ["first", "last", False])
  @pytest.mark.parametrize("subset", [None, ["A", "B"], "A"])
  def test_duplicated_subset(subset, keep):
      df = DataFrame(
          {
              "A": [0, 1, 1, 2, 0],
              "B": ["a", "b", "b", "c", "a"],
              "C": [np.nan, 3, 3, None, np.nan],
          }
      )
  
      if subset is None:
          subset = list(df.columns)
      elif isinstance(subset, str):
          # need to have a DataFrame, not a Series
          # -> select columns with singleton list, not string
          subset = [subset]
  
      expected = df[subset].duplicated(keep=keep)
      result = df.duplicated(keep=keep, subset=subset)
      tm.assert_series_equal(result, expected)
  
  
  def test_drop_duplicates():
      df = DataFrame(
          {
              "AAA": ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
              "B": ["one", "one", "two", "two", "two", "two", "one", "two"],
              "C": [1, 1, 2, 2, 2, 2, 1, 2],
              "D": range(8),
          }
      )
      # single column
      result = df.drop_duplicates("AAA")
      expected = df[:2]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("AAA", keep="last")
      expected = df.loc[[6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("AAA", keep=False)
      expected = df.loc[[]]
      tm.assert_frame_equal(result, expected)
      assert len(result) == 0
  
      # multi column
      expected = df.loc[[0, 1, 2, 3]]
      result = df.drop_duplicates(np.array(["AAA", "B"]))
      tm.assert_frame_equal(result, expected)
      result = df.drop_duplicates(["AAA", "B"])
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(("AAA", "B"), keep="last")
      expected = df.loc[[0, 5, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(("AAA", "B"), keep=False)
      expected = df.loc[[0]]
      tm.assert_frame_equal(result, expected)
  
      # consider everything
      df2 = df.loc[:, ["AAA", "B", "C"]]
  
      result = df2.drop_duplicates()
      # in this case only
      expected = df2.drop_duplicates(["AAA", "B"])
      tm.assert_frame_equal(result, expected)
  
      result = df2.drop_duplicates(keep="last")
      expected = df2.drop_duplicates(["AAA", "B"], keep="last")
      tm.assert_frame_equal(result, expected)
  
      result = df2.drop_duplicates(keep=False)
      expected = df2.drop_duplicates(["AAA", "B"], keep=False)
      tm.assert_frame_equal(result, expected)
  
      # integers
      result = df.drop_duplicates("C")
      expected = df.iloc[[0, 2]]
      tm.assert_frame_equal(result, expected)
      result = df.drop_duplicates("C", keep="last")
      expected = df.iloc[[-2, -1]]
      tm.assert_frame_equal(result, expected)
  
      df["E"] = df["C"].astype("int8")
      result = df.drop_duplicates("E")
      expected = df.iloc[[0, 2]]
      tm.assert_frame_equal(result, expected)
      result = df.drop_duplicates("E", keep="last")
      expected = df.iloc[[-2, -1]]
      tm.assert_frame_equal(result, expected)
  
      # GH 11376
      df = DataFrame({"x": [7, 6, 3, 3, 4, 8, 0], "y": [0, 6, 5, 5, 9, 1, 2]})
      expected = df.loc[df.index != 3]
      tm.assert_frame_equal(df.drop_duplicates(), expected)
  
      df = DataFrame([[1, 0], [0, 2]])
      tm.assert_frame_equal(df.drop_duplicates(), df)
  
      df = DataFrame([[-2, 0], [0, -4]])
      tm.assert_frame_equal(df.drop_duplicates(), df)
  
      x = np.iinfo(np.int64).max / 3 * 2
      df = DataFrame([[-x, x], [0, x + 4]])
      tm.assert_frame_equal(df.drop_duplicates(), df)
  
      df = DataFrame([[-x, x], [x, x + 4]])
      tm.assert_frame_equal(df.drop_duplicates(), df)
  
      # GH 11864
      df = DataFrame([i] * 9 for i in range(16))
      df = df.append([[1] + [0] * 8], ignore_index=True)
  
      for keep in ["first", "last", False]:
          assert df.duplicated(keep=keep).sum() == 0
  
  
  def test_duplicated_on_empty_frame():
      # GH 25184
  
      df = DataFrame(columns=["a", "b"])
      dupes = df.duplicated("a")
  
      result = df[dupes]
      expected = df.copy()
      tm.assert_frame_equal(result, expected)
  
  
  def test_drop_duplicates_with_duplicate_column_names():
      # GH17836
      df = DataFrame([[1, 2, 5], [3, 4, 6], [3, 4, 7]], columns=["a", "a", "b"])
  
      result0 = df.drop_duplicates()
      tm.assert_frame_equal(result0, df)
  
      result1 = df.drop_duplicates("a")
      expected1 = df[:2]
      tm.assert_frame_equal(result1, expected1)
  
  
  def test_drop_duplicates_for_take_all():
      df = DataFrame(
          {
              "AAA": ["foo", "bar", "baz", "bar", "foo", "bar", "qux", "foo"],
              "B": ["one", "one", "two", "two", "two", "two", "one", "two"],
              "C": [1, 1, 2, 2, 2, 2, 1, 2],
              "D": range(8),
          }
      )
      # single column
      result = df.drop_duplicates("AAA")
      expected = df.iloc[[0, 1, 2, 6]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("AAA", keep="last")
      expected = df.iloc[[2, 5, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("AAA", keep=False)
      expected = df.iloc[[2, 6]]
      tm.assert_frame_equal(result, expected)
  
      # multiple columns
      result = df.drop_duplicates(["AAA", "B"])
      expected = df.iloc[[0, 1, 2, 3, 4, 6]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(["AAA", "B"], keep="last")
      expected = df.iloc[[0, 1, 2, 5, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(["AAA", "B"], keep=False)
      expected = df.iloc[[0, 1, 2, 6]]
      tm.assert_frame_equal(result, expected)
  
  
  def test_drop_duplicates_tuple():
      df = DataFrame(
          {
              ("AA", "AB"): ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
              "B": ["one", "one", "two", "two", "two", "two", "one", "two"],
              "C": [1, 1, 2, 2, 2, 2, 1, 2],
              "D": range(8),
          }
      )
      # single column
      result = df.drop_duplicates(("AA", "AB"))
      expected = df[:2]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(("AA", "AB"), keep="last")
      expected = df.loc[[6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(("AA", "AB"), keep=False)
      expected = df.loc[[]]  # empty df
      assert len(result) == 0
      tm.assert_frame_equal(result, expected)
  
      # multi column
      expected = df.loc[[0, 1, 2, 3]]
      result = df.drop_duplicates((("AA", "AB"), "B"))
      tm.assert_frame_equal(result, expected)
  
  
  @pytest.mark.parametrize(
      "df",
      [
          DataFrame(),
          DataFrame(columns=[]),
          DataFrame(columns=["A", "B", "C"]),
          DataFrame(index=[]),
          DataFrame(index=["A", "B", "C"]),
      ],
  )
  def test_drop_duplicates_empty(df):
      # GH 20516
      result = df.drop_duplicates()
      tm.assert_frame_equal(result, df)
  
      result = df.copy()
      result.drop_duplicates(inplace=True)
      tm.assert_frame_equal(result, df)
  
  
  def test_drop_duplicates_NA():
      # none
      df = DataFrame(
          {
              "A": [None, None, "foo", "bar", "foo", "bar", "bar", "foo"],
              "B": ["one", "one", "two", "two", "two", "two", "one", "two"],
              "C": [1.0, np.nan, np.nan, np.nan, 1.0, 1.0, 1, 1.0],
              "D": range(8),
          }
      )
      # single column
      result = df.drop_duplicates("A")
      expected = df.loc[[0, 2, 3]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("A", keep="last")
      expected = df.loc[[1, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("A", keep=False)
      expected = df.loc[[]]  # empty df
      tm.assert_frame_equal(result, expected)
      assert len(result) == 0
  
      # multi column
      result = df.drop_duplicates(["A", "B"])
      expected = df.loc[[0, 2, 3, 6]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(["A", "B"], keep="last")
      expected = df.loc[[1, 5, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(["A", "B"], keep=False)
      expected = df.loc[[6]]
      tm.assert_frame_equal(result, expected)
  
      # nan
      df = DataFrame(
          {
              "A": ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
              "B": ["one", "one", "two", "two", "two", "two", "one", "two"],
              "C": [1.0, np.nan, np.nan, np.nan, 1.0, 1.0, 1, 1.0],
              "D": range(8),
          }
      )
      # single column
      result = df.drop_duplicates("C")
      expected = df[:2]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("C", keep="last")
      expected = df.loc[[3, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("C", keep=False)
      expected = df.loc[[]]  # empty df
      tm.assert_frame_equal(result, expected)
      assert len(result) == 0
  
      # multi column
      result = df.drop_duplicates(["C", "B"])
      expected = df.loc[[0, 1, 2, 4]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(["C", "B"], keep="last")
      expected = df.loc[[1, 3, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates(["C", "B"], keep=False)
      expected = df.loc[[1]]
      tm.assert_frame_equal(result, expected)
  
  
  def test_drop_duplicates_NA_for_take_all():
      # none
      df = DataFrame(
          {
              "A": [None, None, "foo", "bar", "foo", "baz", "bar", "qux"],
              "C": [1.0, np.nan, np.nan, np.nan, 1.0, 2.0, 3, 1.0],
          }
      )
  
      # single column
      result = df.drop_duplicates("A")
      expected = df.iloc[[0, 2, 3, 5, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("A", keep="last")
      expected = df.iloc[[1, 4, 5, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("A", keep=False)
      expected = df.iloc[[5, 7]]
      tm.assert_frame_equal(result, expected)
  
      # nan
  
      # single column
      result = df.drop_duplicates("C")
      expected = df.iloc[[0, 1, 5, 6]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("C", keep="last")
      expected = df.iloc[[3, 5, 6, 7]]
      tm.assert_frame_equal(result, expected)
  
      result = df.drop_duplicates("C", keep=False)
      expected = df.iloc[[5, 6]]
      tm.assert_frame_equal(result, expected)
  
  
  def test_drop_duplicates_inplace():
      orig = DataFrame(
          {
              "A": ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
              "B": ["one", "one", "two", "two", "two", "two", "one", "two"],
              "C": [1, 1, 2, 2, 2, 2, 1, 2],
              "D": range(8),
          }
      )
      # single column
      df = orig.copy()
      df.drop_duplicates("A", inplace=True)
      expected = orig[:2]
      result = df
      tm.assert_frame_equal(result, expected)
  
      df = orig.copy()
      df.drop_duplicates("A", keep="last", inplace=True)
      expected = orig.loc[[6, 7]]
      result = df
      tm.assert_frame_equal(result, expected)
  
      df = orig.copy()
      df.drop_duplicates("A", keep=False, inplace=True)
      expected = orig.loc[[]]
      result = df
      tm.assert_frame_equal(result, expected)
      assert len(df) == 0
  
      # multi column
      df = orig.copy()
      df.drop_duplicates(["A", "B"], inplace=True)
      expected = orig.loc[[0, 1, 2, 3]]
      result = df
      tm.assert_frame_equal(result, expected)
  
      df = orig.copy()
      df.drop_duplicates(["A", "B"], keep="last", inplace=True)
      expected = orig.loc[[0, 5, 6, 7]]
      result = df
      tm.assert_frame_equal(result, expected)
  
      df = orig.copy()
      df.drop_duplicates(["A", "B"], keep=False, inplace=True)
      expected = orig.loc[[0]]
      result = df
      tm.assert_frame_equal(result, expected)
  
      # consider everything
      orig2 = orig.loc[:, ["A", "B", "C"]].copy()
  
      df2 = orig2.copy()
      df2.drop_duplicates(inplace=True)
      # in this case only
      expected = orig2.drop_duplicates(["A", "B"])
      result = df2
      tm.assert_frame_equal(result, expected)
  
      df2 = orig2.copy()
      df2.drop_duplicates(keep="last", inplace=True)
      expected = orig2.drop_duplicates(["A", "B"], keep="last")
      result = df2
      tm.assert_frame_equal(result, expected)
  
      df2 = orig2.copy()
      df2.drop_duplicates(keep=False, inplace=True)
      expected = orig2.drop_duplicates(["A", "B"], keep=False)
      result = df2
      tm.assert_frame_equal(result, expected)
  