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)