393 lines
14 KiB
Python
393 lines
14 KiB
Python
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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Index,
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IndexSlice,
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MultiIndex,
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Series,
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concat,
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)
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import pandas._testing as tm
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import pandas.core.common as com
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from pandas.tseries.offsets import BDay
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@pytest.fixture
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def four_level_index_dataframe():
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arr = np.array(
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[
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[-0.5109, -2.3358, -0.4645, 0.05076, 0.364],
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[0.4473, 1.4152, 0.2834, 1.00661, 0.1744],
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[-0.6662, -0.5243, -0.358, 0.89145, 2.5838],
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]
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)
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index = MultiIndex(
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levels=[["a", "x"], ["b", "q"], [10.0032, 20.0, 30.0], [3, 4, 5]],
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codes=[[0, 0, 1], [0, 1, 1], [0, 1, 2], [2, 1, 0]],
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names=["one", "two", "three", "four"],
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)
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return DataFrame(arr, index=index, columns=list("ABCDE"))
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class TestXS:
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def test_xs(self, float_frame, datetime_frame):
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idx = float_frame.index[5]
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xs = float_frame.xs(idx)
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for item, value in xs.items():
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if np.isnan(value):
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assert np.isnan(float_frame[item][idx])
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else:
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assert value == float_frame[item][idx]
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# mixed-type xs
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test_data = {"A": {"1": 1, "2": 2}, "B": {"1": "1", "2": "2", "3": "3"}}
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frame = DataFrame(test_data)
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xs = frame.xs("1")
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assert xs.dtype == np.object_
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assert xs["A"] == 1
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assert xs["B"] == "1"
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with pytest.raises(
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KeyError, match=re.escape("Timestamp('1999-12-31 00:00:00', freq='B')")
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):
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datetime_frame.xs(datetime_frame.index[0] - BDay())
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# xs get column
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series = float_frame.xs("A", axis=1)
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expected = float_frame["A"]
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tm.assert_series_equal(series, expected)
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# view is returned if possible
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series = float_frame.xs("A", axis=1)
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series[:] = 5
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assert (expected == 5).all()
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def test_xs_corner(self):
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# pathological mixed-type reordering case
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df = DataFrame(index=[0])
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df["A"] = 1.0
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df["B"] = "foo"
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df["C"] = 2.0
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df["D"] = "bar"
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df["E"] = 3.0
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xs = df.xs(0)
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exp = Series([1.0, "foo", 2.0, "bar", 3.0], index=list("ABCDE"), name=0)
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tm.assert_series_equal(xs, exp)
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# no columns but Index(dtype=object)
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df = DataFrame(index=["a", "b", "c"])
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result = df.xs("a")
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expected = Series([], name="a", index=Index([]), dtype=np.float64)
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tm.assert_series_equal(result, expected)
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def test_xs_duplicates(self):
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df = DataFrame(np.random.randn(5, 2), index=["b", "b", "c", "b", "a"])
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cross = df.xs("c")
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exp = df.iloc[2]
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tm.assert_series_equal(cross, exp)
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def test_xs_keep_level(self):
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df = DataFrame(
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{
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"day": {0: "sat", 1: "sun"},
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"flavour": {0: "strawberry", 1: "strawberry"},
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"sales": {0: 10, 1: 12},
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"year": {0: 2008, 1: 2008},
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}
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).set_index(["year", "flavour", "day"])
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result = df.xs("sat", level="day", drop_level=False)
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expected = df[:1]
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tm.assert_frame_equal(result, expected)
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with tm.assert_produces_warning(FutureWarning):
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result = df.xs([2008, "sat"], level=["year", "day"], drop_level=False)
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tm.assert_frame_equal(result, expected)
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def test_xs_view(self, using_array_manager):
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# in 0.14 this will return a view if possible a copy otherwise, but
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# this is numpy dependent
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dm = DataFrame(np.arange(20.0).reshape(4, 5), index=range(4), columns=range(5))
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if using_array_manager:
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# INFO(ArrayManager) with ArrayManager getting a row as a view is
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# not possible
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msg = r"\nA value is trying to be set on a copy of a slice from a DataFrame"
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with pytest.raises(com.SettingWithCopyError, match=msg):
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dm.xs(2)[:] = 20
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assert not (dm.xs(2) == 20).any()
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else:
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dm.xs(2)[:] = 20
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assert (dm.xs(2) == 20).all()
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class TestXSWithMultiIndex:
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def test_xs_doc_example(self):
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# TODO: more descriptive name
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# based on example in advanced.rst
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arrays = [
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["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"],
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["one", "two", "one", "two", "one", "two", "one", "two"],
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]
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tuples = list(zip(*arrays))
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index = MultiIndex.from_tuples(tuples, names=["first", "second"])
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df = DataFrame(np.random.randn(3, 8), index=["A", "B", "C"], columns=index)
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result = df.xs(("one", "bar"), level=("second", "first"), axis=1)
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expected = df.iloc[:, [0]]
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tm.assert_frame_equal(result, expected)
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def test_xs_integer_key(self):
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# see GH#2107
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dates = range(20111201, 20111205)
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ids = list("abcde")
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index = MultiIndex.from_product([dates, ids], names=["date", "secid"])
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df = DataFrame(np.random.randn(len(index), 3), index, ["X", "Y", "Z"])
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result = df.xs(20111201, level="date")
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expected = df.loc[20111201, :]
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tm.assert_frame_equal(result, expected)
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def test_xs_level(self, multiindex_dataframe_random_data):
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df = multiindex_dataframe_random_data
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result = df.xs("two", level="second")
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expected = df[df.index.get_level_values(1) == "two"]
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expected.index = Index(["foo", "bar", "baz", "qux"], name="first")
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tm.assert_frame_equal(result, expected)
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def test_xs_level_eq_2(self):
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arr = np.random.randn(3, 5)
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index = MultiIndex(
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levels=[["a", "p", "x"], ["b", "q", "y"], ["c", "r", "z"]],
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codes=[[2, 0, 1], [2, 0, 1], [2, 0, 1]],
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)
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df = DataFrame(arr, index=index)
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expected = DataFrame(arr[1:2], index=[["a"], ["b"]])
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result = df.xs("c", level=2)
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tm.assert_frame_equal(result, expected)
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def test_xs_setting_with_copy_error(self, multiindex_dataframe_random_data):
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# this is a copy in 0.14
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df = multiindex_dataframe_random_data
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result = df.xs("two", level="second")
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# setting this will give a SettingWithCopyError
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# as we are trying to write a view
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msg = "A value is trying to be set on a copy of a slice from a DataFrame"
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with pytest.raises(com.SettingWithCopyError, match=msg):
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result[:] = 10
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def test_xs_setting_with_copy_error_multiple(self, four_level_index_dataframe):
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# this is a copy in 0.14
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df = four_level_index_dataframe
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result = df.xs(("a", 4), level=["one", "four"])
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# setting this will give a SettingWithCopyError
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# as we are trying to write a view
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msg = "A value is trying to be set on a copy of a slice from a DataFrame"
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with pytest.raises(com.SettingWithCopyError, match=msg):
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result[:] = 10
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@pytest.mark.parametrize("key, level", [("one", "second"), (["one"], ["second"])])
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def test_xs_with_duplicates(self, key, level, multiindex_dataframe_random_data):
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# see GH#13719
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frame = multiindex_dataframe_random_data
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df = concat([frame] * 2)
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assert df.index.is_unique is False
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expected = concat([frame.xs("one", level="second")] * 2)
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if isinstance(key, list):
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with tm.assert_produces_warning(FutureWarning):
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result = df.xs(key, level=level)
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else:
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result = df.xs(key, level=level)
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tm.assert_frame_equal(result, expected)
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def test_xs_missing_values_in_index(self):
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# see GH#6574
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# missing values in returned index should be preserved
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acc = [
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("a", "abcde", 1),
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("b", "bbcde", 2),
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("y", "yzcde", 25),
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("z", "xbcde", 24),
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("z", None, 26),
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("z", "zbcde", 25),
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("z", "ybcde", 26),
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]
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df = DataFrame(acc, columns=["a1", "a2", "cnt"]).set_index(["a1", "a2"])
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expected = DataFrame(
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{"cnt": [24, 26, 25, 26]},
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index=Index(["xbcde", np.nan, "zbcde", "ybcde"], name="a2"),
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)
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result = df.xs("z", level="a1")
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"key, level, exp_arr, exp_index",
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[
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("a", "lvl0", lambda x: x[:, 0:2], Index(["bar", "foo"], name="lvl1")),
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("foo", "lvl1", lambda x: x[:, 1:2], Index(["a"], name="lvl0")),
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],
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)
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def test_xs_named_levels_axis_eq_1(self, key, level, exp_arr, exp_index):
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# see GH#2903
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arr = np.random.randn(4, 4)
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index = MultiIndex(
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levels=[["a", "b"], ["bar", "foo", "hello", "world"]],
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codes=[[0, 0, 1, 1], [0, 1, 2, 3]],
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names=["lvl0", "lvl1"],
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)
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df = DataFrame(arr, columns=index)
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result = df.xs(key, level=level, axis=1)
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expected = DataFrame(exp_arr(arr), columns=exp_index)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"indexer",
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[
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lambda df: df.xs(("a", 4), level=["one", "four"]),
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lambda df: df.xs("a").xs(4, level="four"),
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],
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)
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def test_xs_level_multiple(self, indexer, four_level_index_dataframe):
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df = four_level_index_dataframe
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expected_values = [[0.4473, 1.4152, 0.2834, 1.00661, 0.1744]]
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expected_index = MultiIndex(
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levels=[["q"], [20.0]], codes=[[0], [0]], names=["two", "three"]
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)
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expected = DataFrame(
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expected_values, index=expected_index, columns=list("ABCDE")
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)
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result = indexer(df)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize(
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"indexer", [lambda df: df.xs("a", level=0), lambda df: df.xs("a")]
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)
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def test_xs_level0(self, indexer, four_level_index_dataframe):
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df = four_level_index_dataframe
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expected_values = [
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[-0.5109, -2.3358, -0.4645, 0.05076, 0.364],
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[0.4473, 1.4152, 0.2834, 1.00661, 0.1744],
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]
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expected_index = MultiIndex(
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levels=[["b", "q"], [10.0032, 20.0], [4, 5]],
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codes=[[0, 1], [0, 1], [1, 0]],
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names=["two", "three", "four"],
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)
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expected = DataFrame(
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expected_values, index=expected_index, columns=list("ABCDE")
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)
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result = indexer(df)
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tm.assert_frame_equal(result, expected)
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def test_xs_values(self, multiindex_dataframe_random_data):
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df = multiindex_dataframe_random_data
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result = df.xs(("bar", "two")).values
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expected = df.values[4]
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tm.assert_almost_equal(result, expected)
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def test_xs_loc_equality(self, multiindex_dataframe_random_data):
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df = multiindex_dataframe_random_data
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result = df.xs(("bar", "two"))
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expected = df.loc[("bar", "two")]
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize("klass", [DataFrame, Series])
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def test_xs_IndexSlice_argument_not_implemented(self, klass):
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# GH#35301
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index = MultiIndex(
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levels=[[("foo", "bar", 0), ("foo", "baz", 0), ("foo", "qux", 0)], [0, 1]],
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codes=[[0, 0, 1, 1, 2, 2], [0, 1, 0, 1, 0, 1]],
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)
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obj = DataFrame(np.random.randn(6, 4), index=index)
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if klass is Series:
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obj = obj[0]
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expected = obj.iloc[-2:].droplevel(0)
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result = obj.xs(IndexSlice[("foo", "qux", 0), :])
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tm.assert_equal(result, expected)
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result = obj.loc[IndexSlice[("foo", "qux", 0), :]]
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tm.assert_equal(result, expected)
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@pytest.mark.parametrize("klass", [DataFrame, Series])
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def test_xs_levels_raises(self, klass):
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obj = DataFrame({"A": [1, 2, 3]})
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if klass is Series:
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obj = obj["A"]
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msg = "Index must be a MultiIndex"
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with pytest.raises(TypeError, match=msg):
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obj.xs(0, level="as")
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def test_xs_multiindex_droplevel_false(self):
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# GH#19056
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mi = MultiIndex.from_tuples(
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[("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"]
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)
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df = DataFrame([[1, 2, 3]], columns=mi)
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result = df.xs("a", axis=1, drop_level=False)
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expected = DataFrame(
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[[1, 2]],
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columns=MultiIndex.from_tuples(
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[("a", "x"), ("a", "y")], names=["level1", "level2"]
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),
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)
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tm.assert_frame_equal(result, expected)
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def test_xs_droplevel_false(self):
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# GH#19056
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df = DataFrame([[1, 2, 3]], columns=Index(["a", "b", "c"]))
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result = df.xs("a", axis=1, drop_level=False)
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expected = DataFrame({"a": [1]})
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tm.assert_frame_equal(result, expected)
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def test_xs_droplevel_false_view(self, using_array_manager):
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# GH#37832
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df = DataFrame([[1, 2, 3]], columns=Index(["a", "b", "c"]))
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result = df.xs("a", axis=1, drop_level=False)
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# check that result still views the same data as df
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assert np.shares_memory(result.iloc[:, 0]._values, df.iloc[:, 0]._values)
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# modifying original df also modifies result when having a single block
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df.iloc[0, 0] = 2
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expected = DataFrame({"a": [2]})
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tm.assert_frame_equal(result, expected)
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# with mixed dataframe, modifying the parent doesn't modify result
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# TODO the "split" path behaves differently here as with single block
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df = DataFrame([[1, 2.5, "a"]], columns=Index(["a", "b", "c"]))
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result = df.xs("a", axis=1, drop_level=False)
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df.iloc[0, 0] = 2
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if using_array_manager:
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# Here the behavior is consistent
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expected = DataFrame({"a": [2]})
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else:
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# FIXME: iloc does not update the array inplace using
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# "split" path
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expected = DataFrame({"a": [1]})
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tm.assert_frame_equal(result, expected)
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def test_xs_list_indexer_droplevel_false(self):
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# GH#41760
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mi = MultiIndex.from_tuples([("x", "m", "a"), ("x", "n", "b"), ("y", "o", "c")])
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df = DataFrame([[1, 2, 3], [4, 5, 6]], columns=mi)
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with tm.assert_produces_warning(FutureWarning):
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with pytest.raises(KeyError, match="y"):
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df.xs(["x", "y"], drop_level=False, axis=1)
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