474 lines
14 KiB
Python
474 lines
14 KiB
Python
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from datetime import datetime
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import re
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import numpy as np
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import pytest
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from pandas import (
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DataFrame,
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NaT,
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concat,
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)
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import pandas._testing as tm
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@pytest.mark.parametrize("subset", ["a", ["a"], ["a", "B"]])
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def test_drop_duplicates_with_misspelled_column_name(subset):
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# GH 19730
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df = DataFrame({"A": [0, 0, 1], "B": [0, 0, 1], "C": [0, 0, 1]})
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msg = re.escape("Index(['a'], dtype='object')")
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with pytest.raises(KeyError, match=msg):
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df.drop_duplicates(subset)
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def test_drop_duplicates():
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df = DataFrame(
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{
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"AAA": ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
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"B": ["one", "one", "two", "two", "two", "two", "one", "two"],
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"C": [1, 1, 2, 2, 2, 2, 1, 2],
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"D": range(8),
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}
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)
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# single column
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result = df.drop_duplicates("AAA")
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expected = df[:2]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("AAA", keep="last")
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expected = df.loc[[6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("AAA", keep=False)
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expected = df.loc[[]]
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tm.assert_frame_equal(result, expected)
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assert len(result) == 0
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# multi column
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expected = df.loc[[0, 1, 2, 3]]
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result = df.drop_duplicates(np.array(["AAA", "B"]))
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["AAA", "B"])
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(("AAA", "B"), keep="last")
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expected = df.loc[[0, 5, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(("AAA", "B"), keep=False)
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expected = df.loc[[0]]
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tm.assert_frame_equal(result, expected)
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# consider everything
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df2 = df.loc[:, ["AAA", "B", "C"]]
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result = df2.drop_duplicates()
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# in this case only
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expected = df2.drop_duplicates(["AAA", "B"])
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tm.assert_frame_equal(result, expected)
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result = df2.drop_duplicates(keep="last")
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expected = df2.drop_duplicates(["AAA", "B"], keep="last")
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tm.assert_frame_equal(result, expected)
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result = df2.drop_duplicates(keep=False)
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expected = df2.drop_duplicates(["AAA", "B"], keep=False)
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tm.assert_frame_equal(result, expected)
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# integers
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result = df.drop_duplicates("C")
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expected = df.iloc[[0, 2]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("C", keep="last")
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expected = df.iloc[[-2, -1]]
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tm.assert_frame_equal(result, expected)
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df["E"] = df["C"].astype("int8")
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result = df.drop_duplicates("E")
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expected = df.iloc[[0, 2]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("E", keep="last")
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expected = df.iloc[[-2, -1]]
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tm.assert_frame_equal(result, expected)
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# GH 11376
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df = DataFrame({"x": [7, 6, 3, 3, 4, 8, 0], "y": [0, 6, 5, 5, 9, 1, 2]})
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expected = df.loc[df.index != 3]
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tm.assert_frame_equal(df.drop_duplicates(), expected)
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df = DataFrame([[1, 0], [0, 2]])
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tm.assert_frame_equal(df.drop_duplicates(), df)
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df = DataFrame([[-2, 0], [0, -4]])
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tm.assert_frame_equal(df.drop_duplicates(), df)
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x = np.iinfo(np.int64).max / 3 * 2
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df = DataFrame([[-x, x], [0, x + 4]])
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tm.assert_frame_equal(df.drop_duplicates(), df)
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df = DataFrame([[-x, x], [x, x + 4]])
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tm.assert_frame_equal(df.drop_duplicates(), df)
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# GH 11864
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df = DataFrame([i] * 9 for i in range(16))
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df = concat([df, DataFrame([[1] + [0] * 8])], ignore_index=True)
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for keep in ["first", "last", False]:
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assert df.duplicated(keep=keep).sum() == 0
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def test_drop_duplicates_with_duplicate_column_names():
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# GH17836
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df = DataFrame([[1, 2, 5], [3, 4, 6], [3, 4, 7]], columns=["a", "a", "b"])
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result0 = df.drop_duplicates()
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tm.assert_frame_equal(result0, df)
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result1 = df.drop_duplicates("a")
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expected1 = df[:2]
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tm.assert_frame_equal(result1, expected1)
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def test_drop_duplicates_for_take_all():
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df = DataFrame(
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{
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"AAA": ["foo", "bar", "baz", "bar", "foo", "bar", "qux", "foo"],
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"B": ["one", "one", "two", "two", "two", "two", "one", "two"],
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"C": [1, 1, 2, 2, 2, 2, 1, 2],
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"D": range(8),
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}
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)
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# single column
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result = df.drop_duplicates("AAA")
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expected = df.iloc[[0, 1, 2, 6]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("AAA", keep="last")
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expected = df.iloc[[2, 5, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("AAA", keep=False)
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expected = df.iloc[[2, 6]]
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tm.assert_frame_equal(result, expected)
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# multiple columns
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result = df.drop_duplicates(["AAA", "B"])
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expected = df.iloc[[0, 1, 2, 3, 4, 6]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["AAA", "B"], keep="last")
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expected = df.iloc[[0, 1, 2, 5, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["AAA", "B"], keep=False)
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expected = df.iloc[[0, 1, 2, 6]]
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tm.assert_frame_equal(result, expected)
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def test_drop_duplicates_tuple():
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df = DataFrame(
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{
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("AA", "AB"): ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
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"B": ["one", "one", "two", "two", "two", "two", "one", "two"],
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"C": [1, 1, 2, 2, 2, 2, 1, 2],
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"D": range(8),
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}
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)
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# single column
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result = df.drop_duplicates(("AA", "AB"))
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expected = df[:2]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(("AA", "AB"), keep="last")
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expected = df.loc[[6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(("AA", "AB"), keep=False)
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expected = df.loc[[]] # empty df
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assert len(result) == 0
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tm.assert_frame_equal(result, expected)
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# multi column
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expected = df.loc[[0, 1, 2, 3]]
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result = df.drop_duplicates((("AA", "AB"), "B"))
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"df",
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[
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DataFrame(),
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DataFrame(columns=[]),
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DataFrame(columns=["A", "B", "C"]),
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DataFrame(index=[]),
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DataFrame(index=["A", "B", "C"]),
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],
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)
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def test_drop_duplicates_empty(df):
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# GH 20516
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result = df.drop_duplicates()
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tm.assert_frame_equal(result, df)
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result = df.copy()
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result.drop_duplicates(inplace=True)
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tm.assert_frame_equal(result, df)
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def test_drop_duplicates_NA():
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# none
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df = DataFrame(
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{
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"A": [None, None, "foo", "bar", "foo", "bar", "bar", "foo"],
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"B": ["one", "one", "two", "two", "two", "two", "one", "two"],
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"C": [1.0, np.nan, np.nan, np.nan, 1.0, 1.0, 1, 1.0],
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"D": range(8),
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}
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)
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# single column
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result = df.drop_duplicates("A")
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expected = df.loc[[0, 2, 3]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("A", keep="last")
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expected = df.loc[[1, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("A", keep=False)
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expected = df.loc[[]] # empty df
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tm.assert_frame_equal(result, expected)
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assert len(result) == 0
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# multi column
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result = df.drop_duplicates(["A", "B"])
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expected = df.loc[[0, 2, 3, 6]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["A", "B"], keep="last")
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expected = df.loc[[1, 5, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["A", "B"], keep=False)
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expected = df.loc[[6]]
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tm.assert_frame_equal(result, expected)
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# nan
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df = DataFrame(
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{
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"A": ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
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"B": ["one", "one", "two", "two", "two", "two", "one", "two"],
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"C": [1.0, np.nan, np.nan, np.nan, 1.0, 1.0, 1, 1.0],
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"D": range(8),
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}
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)
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# single column
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result = df.drop_duplicates("C")
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expected = df[:2]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("C", keep="last")
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expected = df.loc[[3, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("C", keep=False)
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expected = df.loc[[]] # empty df
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tm.assert_frame_equal(result, expected)
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assert len(result) == 0
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# multi column
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result = df.drop_duplicates(["C", "B"])
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expected = df.loc[[0, 1, 2, 4]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["C", "B"], keep="last")
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expected = df.loc[[1, 3, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates(["C", "B"], keep=False)
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expected = df.loc[[1]]
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tm.assert_frame_equal(result, expected)
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def test_drop_duplicates_NA_for_take_all():
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# none
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df = DataFrame(
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{
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"A": [None, None, "foo", "bar", "foo", "baz", "bar", "qux"],
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"C": [1.0, np.nan, np.nan, np.nan, 1.0, 2.0, 3, 1.0],
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}
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)
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# single column
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result = df.drop_duplicates("A")
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expected = df.iloc[[0, 2, 3, 5, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("A", keep="last")
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expected = df.iloc[[1, 4, 5, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("A", keep=False)
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expected = df.iloc[[5, 7]]
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tm.assert_frame_equal(result, expected)
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# nan
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# single column
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result = df.drop_duplicates("C")
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expected = df.iloc[[0, 1, 5, 6]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("C", keep="last")
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expected = df.iloc[[3, 5, 6, 7]]
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tm.assert_frame_equal(result, expected)
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result = df.drop_duplicates("C", keep=False)
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expected = df.iloc[[5, 6]]
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tm.assert_frame_equal(result, expected)
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def test_drop_duplicates_inplace():
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orig = DataFrame(
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{
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"A": ["foo", "bar", "foo", "bar", "foo", "bar", "bar", "foo"],
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"B": ["one", "one", "two", "two", "two", "two", "one", "two"],
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"C": [1, 1, 2, 2, 2, 2, 1, 2],
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"D": range(8),
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}
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)
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# single column
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df = orig.copy()
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return_value = df.drop_duplicates("A", inplace=True)
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expected = orig[:2]
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result = df
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tm.assert_frame_equal(result, expected)
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assert return_value is None
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df = orig.copy()
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return_value = df.drop_duplicates("A", keep="last", inplace=True)
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expected = orig.loc[[6, 7]]
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result = df
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tm.assert_frame_equal(result, expected)
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assert return_value is None
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|
|
df = orig.copy()
|
||
|
|
return_value = df.drop_duplicates("A", keep=False, inplace=True)
|
||
|
|
expected = orig.loc[[]]
|
||
|
|
result = df
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert len(df) == 0
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
# multi column
|
||
|
|
df = orig.copy()
|
||
|
|
return_value = df.drop_duplicates(["A", "B"], inplace=True)
|
||
|
|
expected = orig.loc[[0, 1, 2, 3]]
|
||
|
|
result = df
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
df = orig.copy()
|
||
|
|
return_value = df.drop_duplicates(["A", "B"], keep="last", inplace=True)
|
||
|
|
expected = orig.loc[[0, 5, 6, 7]]
|
||
|
|
result = df
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
df = orig.copy()
|
||
|
|
return_value = df.drop_duplicates(["A", "B"], keep=False, inplace=True)
|
||
|
|
expected = orig.loc[[0]]
|
||
|
|
result = df
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
# consider everything
|
||
|
|
orig2 = orig.loc[:, ["A", "B", "C"]].copy()
|
||
|
|
|
||
|
|
df2 = orig2.copy()
|
||
|
|
return_value = df2.drop_duplicates(inplace=True)
|
||
|
|
# in this case only
|
||
|
|
expected = orig2.drop_duplicates(["A", "B"])
|
||
|
|
result = df2
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
df2 = orig2.copy()
|
||
|
|
return_value = df2.drop_duplicates(keep="last", inplace=True)
|
||
|
|
expected = orig2.drop_duplicates(["A", "B"], keep="last")
|
||
|
|
result = df2
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
df2 = orig2.copy()
|
||
|
|
return_value = df2.drop_duplicates(keep=False, inplace=True)
|
||
|
|
expected = orig2.drop_duplicates(["A", "B"], keep=False)
|
||
|
|
result = df2
|
||
|
|
tm.assert_frame_equal(result, expected)
|
||
|
|
assert return_value is None
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("inplace", [True, False])
|
||
|
|
@pytest.mark.parametrize(
|
||
|
|
"origin_dict, output_dict, ignore_index, output_index",
|
||
|
|
[
|
||
|
|
({"A": [2, 2, 3]}, {"A": [2, 3]}, True, [0, 1]),
|
||
|
|
({"A": [2, 2, 3]}, {"A": [2, 3]}, False, [0, 2]),
|
||
|
|
({"A": [2, 2, 3], "B": [2, 2, 4]}, {"A": [2, 3], "B": [2, 4]}, True, [0, 1]),
|
||
|
|
({"A": [2, 2, 3], "B": [2, 2, 4]}, {"A": [2, 3], "B": [2, 4]}, False, [0, 2]),
|
||
|
|
],
|
||
|
|
)
|
||
|
|
def test_drop_duplicates_ignore_index(
|
||
|
|
inplace, origin_dict, output_dict, ignore_index, output_index
|
||
|
|
):
|
||
|
|
# GH 30114
|
||
|
|
df = DataFrame(origin_dict)
|
||
|
|
expected = DataFrame(output_dict, index=output_index)
|
||
|
|
|
||
|
|
if inplace:
|
||
|
|
result_df = df.copy()
|
||
|
|
result_df.drop_duplicates(ignore_index=ignore_index, inplace=inplace)
|
||
|
|
else:
|
||
|
|
result_df = df.drop_duplicates(ignore_index=ignore_index, inplace=inplace)
|
||
|
|
|
||
|
|
tm.assert_frame_equal(result_df, expected)
|
||
|
|
tm.assert_frame_equal(df, DataFrame(origin_dict))
|
||
|
|
|
||
|
|
|
||
|
|
def test_drop_duplicates_null_in_object_column(nulls_fixture):
|
||
|
|
# https://github.com/pandas-dev/pandas/issues/32992
|
||
|
|
df = DataFrame([[1, nulls_fixture], [2, "a"]], dtype=object)
|
||
|
|
result = df.drop_duplicates()
|
||
|
|
tm.assert_frame_equal(result, df)
|
||
|
|
|
||
|
|
|
||
|
|
def test_drop_duplicates_series_vs_dataframe(keep):
|
||
|
|
# GH#14192
|
||
|
|
df = DataFrame(
|
||
|
|
{
|
||
|
|
"a": [1, 1, 1, "one", "one"],
|
||
|
|
"b": [2, 2, np.nan, np.nan, np.nan],
|
||
|
|
"c": [3, 3, np.nan, np.nan, "three"],
|
||
|
|
"d": [1, 2, 3, 4, 4],
|
||
|
|
"e": [
|
||
|
|
datetime(2015, 1, 1),
|
||
|
|
datetime(2015, 1, 1),
|
||
|
|
datetime(2015, 2, 1),
|
||
|
|
NaT,
|
||
|
|
NaT,
|
||
|
|
],
|
||
|
|
}
|
||
|
|
)
|
||
|
|
for column in df.columns:
|
||
|
|
dropped_frame = df[[column]].drop_duplicates(keep=keep)
|
||
|
|
dropped_series = df[column].drop_duplicates(keep=keep)
|
||
|
|
tm.assert_frame_equal(dropped_frame, dropped_series.to_frame())
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("arg", [[1], 1, "True", [], 0])
|
||
|
|
def test_drop_duplicates_non_boolean_ignore_index(arg):
|
||
|
|
# GH#38274
|
||
|
|
df = DataFrame({"a": [1, 2, 1, 3]})
|
||
|
|
msg = '^For argument "ignore_index" expected type bool, received type .*.$'
|
||
|
|
with pytest.raises(ValueError, match=msg):
|
||
|
|
df.drop_duplicates(ignore_index=arg)
|