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| import numpy as np
| import pytest
|
| import pandas as pd
| from pandas import (
| DataFrame,
| MultiIndex,
| Series,
| )
| import pandas._testing as tm
|
|
| class TestDataFrameIsIn:
| def test_isin(self):
| # GH#4211
| df = DataFrame(
| {
| "vals": [1, 2, 3, 4],
| "ids": ["a", "b", "f", "n"],
| "ids2": ["a", "n", "c", "n"],
| },
| index=["foo", "bar", "baz", "qux"],
| )
| other = ["a", "b", "c"]
|
| result = df.isin(other)
| expected = DataFrame([df.loc[s].isin(other) for s in df.index])
| tm.assert_frame_equal(result, expected)
|
| @pytest.mark.parametrize("empty", [[], Series(dtype=object), np.array([])])
| def test_isin_empty(self, empty):
| # GH#16991
| df = DataFrame({"A": ["a", "b", "c"], "B": ["a", "e", "f"]})
| expected = DataFrame(False, df.index, df.columns)
|
| result = df.isin(empty)
| tm.assert_frame_equal(result, expected)
|
| def test_isin_dict(self):
| df = DataFrame({"A": ["a", "b", "c"], "B": ["a", "e", "f"]})
| d = {"A": ["a"]}
|
| expected = DataFrame(False, df.index, df.columns)
| expected.loc[0, "A"] = True
|
| result = df.isin(d)
| tm.assert_frame_equal(result, expected)
|
| # non unique columns
| df = DataFrame({"A": ["a", "b", "c"], "B": ["a", "e", "f"]})
| df.columns = ["A", "A"]
| expected = DataFrame(False, df.index, df.columns)
| expected.loc[0, "A"] = True
| result = df.isin(d)
| tm.assert_frame_equal(result, expected)
|
| def test_isin_with_string_scalar(self):
| # GH#4763
| df = DataFrame(
| {
| "vals": [1, 2, 3, 4],
| "ids": ["a", "b", "f", "n"],
| "ids2": ["a", "n", "c", "n"],
| },
| index=["foo", "bar", "baz", "qux"],
| )
| msg = (
| r"only list-like or dict-like objects are allowed "
| r"to be passed to DataFrame.isin\(\), you passed a 'str'"
| )
| with pytest.raises(TypeError, match=msg):
| df.isin("a")
|
| with pytest.raises(TypeError, match=msg):
| df.isin("aaa")
|
| def test_isin_df(self):
| df1 = DataFrame({"A": [1, 2, 3, 4], "B": [2, np.nan, 4, 4]})
| df2 = DataFrame({"A": [0, 2, 12, 4], "B": [2, np.nan, 4, 5]})
| expected = DataFrame(False, df1.index, df1.columns)
| result = df1.isin(df2)
| expected.loc[[1, 3], "A"] = True
| expected.loc[[0, 2], "B"] = True
| tm.assert_frame_equal(result, expected)
|
| # partial overlapping columns
| df2.columns = ["A", "C"]
| result = df1.isin(df2)
| expected["B"] = False
| tm.assert_frame_equal(result, expected)
|
| def test_isin_tuples(self):
| # GH#16394
| df = DataFrame({"A": [1, 2, 3], "B": ["a", "b", "f"]})
| df["C"] = list(zip(df["A"], df["B"]))
| result = df["C"].isin([(1, "a")])
| tm.assert_series_equal(result, Series([True, False, False], name="C"))
|
| def test_isin_df_dupe_values(self):
| df1 = DataFrame({"A": [1, 2, 3, 4], "B": [2, np.nan, 4, 4]})
| # just cols duped
| df2 = DataFrame([[0, 2], [12, 4], [2, np.nan], [4, 5]], columns=["B", "B"])
| msg = r"cannot compute isin with a duplicate axis\."
| with pytest.raises(ValueError, match=msg):
| df1.isin(df2)
|
| # just index duped
| df2 = DataFrame(
| [[0, 2], [12, 4], [2, np.nan], [4, 5]],
| columns=["A", "B"],
| index=[0, 0, 1, 1],
| )
| with pytest.raises(ValueError, match=msg):
| df1.isin(df2)
|
| # cols and index:
| df2.columns = ["B", "B"]
| with pytest.raises(ValueError, match=msg):
| df1.isin(df2)
|
| def test_isin_dupe_self(self):
| other = DataFrame({"A": [1, 0, 1, 0], "B": [1, 1, 0, 0]})
| df = DataFrame([[1, 1], [1, 0], [0, 0]], columns=["A", "A"])
| result = df.isin(other)
| expected = DataFrame(False, index=df.index, columns=df.columns)
| expected.loc[0] = True
| expected.iloc[1, 1] = True
| tm.assert_frame_equal(result, expected)
|
| def test_isin_against_series(self):
| df = DataFrame(
| {"A": [1, 2, 3, 4], "B": [2, np.nan, 4, 4]}, index=["a", "b", "c", "d"]
| )
| s = Series([1, 3, 11, 4], index=["a", "b", "c", "d"])
| expected = DataFrame(False, index=df.index, columns=df.columns)
| expected.loc["a", "A"] = True
| expected.loc["d"] = True
| result = df.isin(s)
| tm.assert_frame_equal(result, expected)
|
| def test_isin_multiIndex(self):
| idx = MultiIndex.from_tuples(
| [
| (0, "a", "foo"),
| (0, "a", "bar"),
| (0, "b", "bar"),
| (0, "b", "baz"),
| (2, "a", "foo"),
| (2, "a", "bar"),
| (2, "c", "bar"),
| (2, "c", "baz"),
| (1, "b", "foo"),
| (1, "b", "bar"),
| (1, "c", "bar"),
| (1, "c", "baz"),
| ]
| )
| df1 = DataFrame({"A": np.ones(12), "B": np.zeros(12)}, index=idx)
| df2 = DataFrame(
| {
| "A": [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1],
| "B": [1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1],
| }
| )
| # against regular index
| expected = DataFrame(False, index=df1.index, columns=df1.columns)
| result = df1.isin(df2)
| tm.assert_frame_equal(result, expected)
|
| df2.index = idx
| expected = df2.values.astype(bool)
| expected[:, 1] = ~expected[:, 1]
| expected = DataFrame(expected, columns=["A", "B"], index=idx)
|
| result = df1.isin(df2)
| tm.assert_frame_equal(result, expected)
|
| def test_isin_empty_datetimelike(self):
| # GH#15473
| df1_ts = DataFrame({"date": pd.to_datetime(["2014-01-01", "2014-01-02"])})
| df1_td = DataFrame({"date": [pd.Timedelta(1, "s"), pd.Timedelta(2, "s")]})
| df2 = DataFrame({"date": []})
| df3 = DataFrame()
|
| expected = DataFrame({"date": [False, False]})
|
| result = df1_ts.isin(df2)
| tm.assert_frame_equal(result, expected)
| result = df1_ts.isin(df3)
| tm.assert_frame_equal(result, expected)
|
| result = df1_td.isin(df2)
| tm.assert_frame_equal(result, expected)
| result = df1_td.isin(df3)
| tm.assert_frame_equal(result, expected)
|
| @pytest.mark.parametrize(
| "values",
| [
| DataFrame({"a": [1, 2, 3]}, dtype="category"),
| Series([1, 2, 3], dtype="category"),
| ],
| )
| def test_isin_category_frame(self, values):
| # GH#34256
| df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
| expected = DataFrame({"a": [True, True, True], "b": [False, False, False]})
|
| result = df.isin(values)
| tm.assert_frame_equal(result, expected)
|
| def test_isin_read_only(self):
| # https://github.com/pandas-dev/pandas/issues/37174
| arr = np.array([1, 2, 3])
| arr.setflags(write=False)
| df = DataFrame([1, 2, 3])
| result = df.isin(arr)
| expected = DataFrame([True, True, True])
| tm.assert_frame_equal(result, expected)
|
|
