You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
392 lines
14 KiB
392 lines
14 KiB
import re
|
|
|
|
import numpy as np
|
|
import pytest
|
|
|
|
from pandas import (
|
|
DataFrame,
|
|
Index,
|
|
IndexSlice,
|
|
MultiIndex,
|
|
Series,
|
|
concat,
|
|
)
|
|
import pandas._testing as tm
|
|
import pandas.core.common as com
|
|
|
|
from pandas.tseries.offsets import BDay
|
|
|
|
|
|
@pytest.fixture
|
|
def four_level_index_dataframe():
|
|
arr = np.array(
|
|
[
|
|
[-0.5109, -2.3358, -0.4645, 0.05076, 0.364],
|
|
[0.4473, 1.4152, 0.2834, 1.00661, 0.1744],
|
|
[-0.6662, -0.5243, -0.358, 0.89145, 2.5838],
|
|
]
|
|
)
|
|
index = MultiIndex(
|
|
levels=[["a", "x"], ["b", "q"], [10.0032, 20.0, 30.0], [3, 4, 5]],
|
|
codes=[[0, 0, 1], [0, 1, 1], [0, 1, 2], [2, 1, 0]],
|
|
names=["one", "two", "three", "four"],
|
|
)
|
|
return DataFrame(arr, index=index, columns=list("ABCDE"))
|
|
|
|
|
|
class TestXS:
|
|
def test_xs(self, float_frame, datetime_frame):
|
|
idx = float_frame.index[5]
|
|
xs = float_frame.xs(idx)
|
|
for item, value in xs.items():
|
|
if np.isnan(value):
|
|
assert np.isnan(float_frame[item][idx])
|
|
else:
|
|
assert value == float_frame[item][idx]
|
|
|
|
# mixed-type xs
|
|
test_data = {"A": {"1": 1, "2": 2}, "B": {"1": "1", "2": "2", "3": "3"}}
|
|
frame = DataFrame(test_data)
|
|
xs = frame.xs("1")
|
|
assert xs.dtype == np.object_
|
|
assert xs["A"] == 1
|
|
assert xs["B"] == "1"
|
|
|
|
with pytest.raises(
|
|
KeyError, match=re.escape("Timestamp('1999-12-31 00:00:00', freq='B')")
|
|
):
|
|
datetime_frame.xs(datetime_frame.index[0] - BDay())
|
|
|
|
# xs get column
|
|
series = float_frame.xs("A", axis=1)
|
|
expected = float_frame["A"]
|
|
tm.assert_series_equal(series, expected)
|
|
|
|
# view is returned if possible
|
|
series = float_frame.xs("A", axis=1)
|
|
series[:] = 5
|
|
assert (expected == 5).all()
|
|
|
|
def test_xs_corner(self):
|
|
# pathological mixed-type reordering case
|
|
df = DataFrame(index=[0])
|
|
df["A"] = 1.0
|
|
df["B"] = "foo"
|
|
df["C"] = 2.0
|
|
df["D"] = "bar"
|
|
df["E"] = 3.0
|
|
|
|
xs = df.xs(0)
|
|
exp = Series([1.0, "foo", 2.0, "bar", 3.0], index=list("ABCDE"), name=0)
|
|
tm.assert_series_equal(xs, exp)
|
|
|
|
# no columns but Index(dtype=object)
|
|
df = DataFrame(index=["a", "b", "c"])
|
|
result = df.xs("a")
|
|
expected = Series([], name="a", index=Index([]), dtype=np.float64)
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
def test_xs_duplicates(self):
|
|
df = DataFrame(np.random.randn(5, 2), index=["b", "b", "c", "b", "a"])
|
|
|
|
cross = df.xs("c")
|
|
exp = df.iloc[2]
|
|
tm.assert_series_equal(cross, exp)
|
|
|
|
def test_xs_keep_level(self):
|
|
df = DataFrame(
|
|
{
|
|
"day": {0: "sat", 1: "sun"},
|
|
"flavour": {0: "strawberry", 1: "strawberry"},
|
|
"sales": {0: 10, 1: 12},
|
|
"year": {0: 2008, 1: 2008},
|
|
}
|
|
).set_index(["year", "flavour", "day"])
|
|
result = df.xs("sat", level="day", drop_level=False)
|
|
expected = df[:1]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
result = df.xs([2008, "sat"], level=["year", "day"], drop_level=False)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_view(self, using_array_manager):
|
|
# in 0.14 this will return a view if possible a copy otherwise, but
|
|
# this is numpy dependent
|
|
|
|
dm = DataFrame(np.arange(20.0).reshape(4, 5), index=range(4), columns=range(5))
|
|
|
|
if using_array_manager:
|
|
# INFO(ArrayManager) with ArrayManager getting a row as a view is
|
|
# not possible
|
|
msg = r"\nA value is trying to be set on a copy of a slice from a DataFrame"
|
|
with pytest.raises(com.SettingWithCopyError, match=msg):
|
|
dm.xs(2)[:] = 20
|
|
assert not (dm.xs(2) == 20).any()
|
|
else:
|
|
dm.xs(2)[:] = 20
|
|
assert (dm.xs(2) == 20).all()
|
|
|
|
|
|
class TestXSWithMultiIndex:
|
|
def test_xs_doc_example(self):
|
|
# TODO: more descriptive name
|
|
# based on example in advanced.rst
|
|
arrays = [
|
|
["bar", "bar", "baz", "baz", "foo", "foo", "qux", "qux"],
|
|
["one", "two", "one", "two", "one", "two", "one", "two"],
|
|
]
|
|
tuples = list(zip(*arrays))
|
|
|
|
index = MultiIndex.from_tuples(tuples, names=["first", "second"])
|
|
df = DataFrame(np.random.randn(3, 8), index=["A", "B", "C"], columns=index)
|
|
|
|
result = df.xs(("one", "bar"), level=("second", "first"), axis=1)
|
|
|
|
expected = df.iloc[:, [0]]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_integer_key(self):
|
|
# see GH#2107
|
|
dates = range(20111201, 20111205)
|
|
ids = list("abcde")
|
|
index = MultiIndex.from_product([dates, ids], names=["date", "secid"])
|
|
df = DataFrame(np.random.randn(len(index), 3), index, ["X", "Y", "Z"])
|
|
|
|
result = df.xs(20111201, level="date")
|
|
expected = df.loc[20111201, :]
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_level(self, multiindex_dataframe_random_data):
|
|
df = multiindex_dataframe_random_data
|
|
result = df.xs("two", level="second")
|
|
expected = df[df.index.get_level_values(1) == "two"]
|
|
expected.index = Index(["foo", "bar", "baz", "qux"], name="first")
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_level_eq_2(self):
|
|
arr = np.random.randn(3, 5)
|
|
index = MultiIndex(
|
|
levels=[["a", "p", "x"], ["b", "q", "y"], ["c", "r", "z"]],
|
|
codes=[[2, 0, 1], [2, 0, 1], [2, 0, 1]],
|
|
)
|
|
df = DataFrame(arr, index=index)
|
|
expected = DataFrame(arr[1:2], index=[["a"], ["b"]])
|
|
result = df.xs("c", level=2)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_setting_with_copy_error(self, multiindex_dataframe_random_data):
|
|
# this is a copy in 0.14
|
|
df = multiindex_dataframe_random_data
|
|
result = df.xs("two", level="second")
|
|
|
|
# setting this will give a SettingWithCopyError
|
|
# as we are trying to write a view
|
|
msg = "A value is trying to be set on a copy of a slice from a DataFrame"
|
|
with pytest.raises(com.SettingWithCopyError, match=msg):
|
|
result[:] = 10
|
|
|
|
def test_xs_setting_with_copy_error_multiple(self, four_level_index_dataframe):
|
|
# this is a copy in 0.14
|
|
df = four_level_index_dataframe
|
|
result = df.xs(("a", 4), level=["one", "four"])
|
|
|
|
# setting this will give a SettingWithCopyError
|
|
# as we are trying to write a view
|
|
msg = "A value is trying to be set on a copy of a slice from a DataFrame"
|
|
with pytest.raises(com.SettingWithCopyError, match=msg):
|
|
result[:] = 10
|
|
|
|
@pytest.mark.parametrize("key, level", [("one", "second"), (["one"], ["second"])])
|
|
def test_xs_with_duplicates(self, key, level, multiindex_dataframe_random_data):
|
|
# see GH#13719
|
|
frame = multiindex_dataframe_random_data
|
|
df = concat([frame] * 2)
|
|
assert df.index.is_unique is False
|
|
expected = concat([frame.xs("one", level="second")] * 2)
|
|
|
|
if isinstance(key, list):
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
result = df.xs(key, level=level)
|
|
else:
|
|
result = df.xs(key, level=level)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_missing_values_in_index(self):
|
|
# see GH#6574
|
|
# missing values in returned index should be preserved
|
|
acc = [
|
|
("a", "abcde", 1),
|
|
("b", "bbcde", 2),
|
|
("y", "yzcde", 25),
|
|
("z", "xbcde", 24),
|
|
("z", None, 26),
|
|
("z", "zbcde", 25),
|
|
("z", "ybcde", 26),
|
|
]
|
|
df = DataFrame(acc, columns=["a1", "a2", "cnt"]).set_index(["a1", "a2"])
|
|
expected = DataFrame(
|
|
{"cnt": [24, 26, 25, 26]},
|
|
index=Index(["xbcde", np.nan, "zbcde", "ybcde"], name="a2"),
|
|
)
|
|
|
|
result = df.xs("z", level="a1")
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"key, level, exp_arr, exp_index",
|
|
[
|
|
("a", "lvl0", lambda x: x[:, 0:2], Index(["bar", "foo"], name="lvl1")),
|
|
("foo", "lvl1", lambda x: x[:, 1:2], Index(["a"], name="lvl0")),
|
|
],
|
|
)
|
|
def test_xs_named_levels_axis_eq_1(self, key, level, exp_arr, exp_index):
|
|
# see GH#2903
|
|
arr = np.random.randn(4, 4)
|
|
index = MultiIndex(
|
|
levels=[["a", "b"], ["bar", "foo", "hello", "world"]],
|
|
codes=[[0, 0, 1, 1], [0, 1, 2, 3]],
|
|
names=["lvl0", "lvl1"],
|
|
)
|
|
df = DataFrame(arr, columns=index)
|
|
result = df.xs(key, level=level, axis=1)
|
|
expected = DataFrame(exp_arr(arr), columns=exp_index)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"indexer",
|
|
[
|
|
lambda df: df.xs(("a", 4), level=["one", "four"]),
|
|
lambda df: df.xs("a").xs(4, level="four"),
|
|
],
|
|
)
|
|
def test_xs_level_multiple(self, indexer, four_level_index_dataframe):
|
|
df = four_level_index_dataframe
|
|
expected_values = [[0.4473, 1.4152, 0.2834, 1.00661, 0.1744]]
|
|
expected_index = MultiIndex(
|
|
levels=[["q"], [20.0]], codes=[[0], [0]], names=["two", "three"]
|
|
)
|
|
expected = DataFrame(
|
|
expected_values, index=expected_index, columns=list("ABCDE")
|
|
)
|
|
result = indexer(df)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize(
|
|
"indexer", [lambda df: df.xs("a", level=0), lambda df: df.xs("a")]
|
|
)
|
|
def test_xs_level0(self, indexer, four_level_index_dataframe):
|
|
df = four_level_index_dataframe
|
|
expected_values = [
|
|
[-0.5109, -2.3358, -0.4645, 0.05076, 0.364],
|
|
[0.4473, 1.4152, 0.2834, 1.00661, 0.1744],
|
|
]
|
|
expected_index = MultiIndex(
|
|
levels=[["b", "q"], [10.0032, 20.0], [4, 5]],
|
|
codes=[[0, 1], [0, 1], [1, 0]],
|
|
names=["two", "three", "four"],
|
|
)
|
|
expected = DataFrame(
|
|
expected_values, index=expected_index, columns=list("ABCDE")
|
|
)
|
|
|
|
result = indexer(df)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_values(self, multiindex_dataframe_random_data):
|
|
df = multiindex_dataframe_random_data
|
|
result = df.xs(("bar", "two")).values
|
|
expected = df.values[4]
|
|
tm.assert_almost_equal(result, expected)
|
|
|
|
def test_xs_loc_equality(self, multiindex_dataframe_random_data):
|
|
df = multiindex_dataframe_random_data
|
|
result = df.xs(("bar", "two"))
|
|
expected = df.loc[("bar", "two")]
|
|
tm.assert_series_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize("klass", [DataFrame, Series])
|
|
def test_xs_IndexSlice_argument_not_implemented(self, klass):
|
|
# GH#35301
|
|
|
|
index = MultiIndex(
|
|
levels=[[("foo", "bar", 0), ("foo", "baz", 0), ("foo", "qux", 0)], [0, 1]],
|
|
codes=[[0, 0, 1, 1, 2, 2], [0, 1, 0, 1, 0, 1]],
|
|
)
|
|
|
|
obj = DataFrame(np.random.randn(6, 4), index=index)
|
|
if klass is Series:
|
|
obj = obj[0]
|
|
|
|
expected = obj.iloc[-2:].droplevel(0)
|
|
|
|
result = obj.xs(IndexSlice[("foo", "qux", 0), :])
|
|
tm.assert_equal(result, expected)
|
|
|
|
result = obj.loc[IndexSlice[("foo", "qux", 0), :]]
|
|
tm.assert_equal(result, expected)
|
|
|
|
@pytest.mark.parametrize("klass", [DataFrame, Series])
|
|
def test_xs_levels_raises(self, klass):
|
|
obj = DataFrame({"A": [1, 2, 3]})
|
|
if klass is Series:
|
|
obj = obj["A"]
|
|
|
|
msg = "Index must be a MultiIndex"
|
|
with pytest.raises(TypeError, match=msg):
|
|
obj.xs(0, level="as")
|
|
|
|
def test_xs_multiindex_droplevel_false(self):
|
|
# GH#19056
|
|
mi = MultiIndex.from_tuples(
|
|
[("a", "x"), ("a", "y"), ("b", "x")], names=["level1", "level2"]
|
|
)
|
|
df = DataFrame([[1, 2, 3]], columns=mi)
|
|
result = df.xs("a", axis=1, drop_level=False)
|
|
expected = DataFrame(
|
|
[[1, 2]],
|
|
columns=MultiIndex.from_tuples(
|
|
[("a", "x"), ("a", "y")], names=["level1", "level2"]
|
|
),
|
|
)
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_droplevel_false(self):
|
|
# GH#19056
|
|
df = DataFrame([[1, 2, 3]], columns=Index(["a", "b", "c"]))
|
|
result = df.xs("a", axis=1, drop_level=False)
|
|
expected = DataFrame({"a": [1]})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_droplevel_false_view(self, using_array_manager):
|
|
# GH#37832
|
|
df = DataFrame([[1, 2, 3]], columns=Index(["a", "b", "c"]))
|
|
result = df.xs("a", axis=1, drop_level=False)
|
|
# check that result still views the same data as df
|
|
assert np.shares_memory(result.iloc[:, 0]._values, df.iloc[:, 0]._values)
|
|
# modifying original df also modifies result when having a single block
|
|
df.iloc[0, 0] = 2
|
|
expected = DataFrame({"a": [2]})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
# with mixed dataframe, modifying the parent doesn't modify result
|
|
# TODO the "split" path behaves differently here as with single block
|
|
df = DataFrame([[1, 2.5, "a"]], columns=Index(["a", "b", "c"]))
|
|
result = df.xs("a", axis=1, drop_level=False)
|
|
df.iloc[0, 0] = 2
|
|
if using_array_manager:
|
|
# Here the behavior is consistent
|
|
expected = DataFrame({"a": [2]})
|
|
else:
|
|
# FIXME: iloc does not update the array inplace using
|
|
# "split" path
|
|
expected = DataFrame({"a": [1]})
|
|
tm.assert_frame_equal(result, expected)
|
|
|
|
def test_xs_list_indexer_droplevel_false(self):
|
|
# GH#41760
|
|
mi = MultiIndex.from_tuples([("x", "m", "a"), ("x", "n", "b"), ("y", "o", "c")])
|
|
df = DataFrame([[1, 2, 3], [4, 5, 6]], columns=mi)
|
|
with tm.assert_produces_warning(FutureWarning):
|
|
with pytest.raises(KeyError, match="y"):
|
|
df.xs(["x", "y"], drop_level=False, axis=1)
|
|
|