projektAI/venv/Lib/site-packages/pandas/tests/indexes/multi/test_equivalence.py
2021-06-06 22:13:05 +02:00

269 lines
8.0 KiB
Python

import numpy as np
import pytest
import pandas as pd
from pandas import Index, MultiIndex, Series
import pandas._testing as tm
def test_equals(idx):
assert idx.equals(idx)
assert idx.equals(idx.copy())
assert idx.equals(idx.astype(object))
assert not idx.equals(list(idx))
assert not idx.equals(np.array(idx))
same_values = Index(idx, dtype=object)
assert idx.equals(same_values)
assert same_values.equals(idx)
if idx.nlevels == 1:
# do not test MultiIndex
assert not idx.equals(Series(idx))
def test_equals_op(idx):
# GH9947, GH10637
index_a = idx
n = len(index_a)
index_b = index_a[0:-1]
index_c = index_a[0:-1].append(index_a[-2:-1])
index_d = index_a[0:1]
with pytest.raises(ValueError, match="Lengths must match"):
index_a == index_b
expected1 = np.array([True] * n)
expected2 = np.array([True] * (n - 1) + [False])
tm.assert_numpy_array_equal(index_a == index_a, expected1)
tm.assert_numpy_array_equal(index_a == index_c, expected2)
# test comparisons with numpy arrays
array_a = np.array(index_a)
array_b = np.array(index_a[0:-1])
array_c = np.array(index_a[0:-1].append(index_a[-2:-1]))
array_d = np.array(index_a[0:1])
with pytest.raises(ValueError, match="Lengths must match"):
index_a == array_b
tm.assert_numpy_array_equal(index_a == array_a, expected1)
tm.assert_numpy_array_equal(index_a == array_c, expected2)
# test comparisons with Series
series_a = Series(array_a)
series_b = Series(array_b)
series_c = Series(array_c)
series_d = Series(array_d)
with pytest.raises(ValueError, match="Lengths must match"):
index_a == series_b
tm.assert_numpy_array_equal(index_a == series_a, expected1)
tm.assert_numpy_array_equal(index_a == series_c, expected2)
# cases where length is 1 for one of them
with pytest.raises(ValueError, match="Lengths must match"):
index_a == index_d
with pytest.raises(ValueError, match="Lengths must match"):
index_a == series_d
with pytest.raises(ValueError, match="Lengths must match"):
index_a == array_d
msg = "Can only compare identically-labeled Series objects"
with pytest.raises(ValueError, match=msg):
series_a == series_d
with pytest.raises(ValueError, match="Lengths must match"):
series_a == array_d
# comparing with a scalar should broadcast; note that we are excluding
# MultiIndex because in this case each item in the index is a tuple of
# length 2, and therefore is considered an array of length 2 in the
# comparison instead of a scalar
if not isinstance(index_a, MultiIndex):
expected3 = np.array([False] * (len(index_a) - 2) + [True, False])
# assuming the 2nd to last item is unique in the data
item = index_a[-2]
tm.assert_numpy_array_equal(index_a == item, expected3)
tm.assert_series_equal(series_a == item, Series(expected3))
def test_compare_tuple():
# GH#21517
mi = MultiIndex.from_product([[1, 2]] * 2)
all_false = np.array([False, False, False, False])
result = mi == mi[0]
expected = np.array([True, False, False, False])
tm.assert_numpy_array_equal(result, expected)
result = mi != mi[0]
tm.assert_numpy_array_equal(result, ~expected)
result = mi < mi[0]
tm.assert_numpy_array_equal(result, all_false)
result = mi <= mi[0]
tm.assert_numpy_array_equal(result, expected)
result = mi > mi[0]
tm.assert_numpy_array_equal(result, ~expected)
result = mi >= mi[0]
tm.assert_numpy_array_equal(result, ~all_false)
def test_compare_tuple_strs():
# GH#34180
mi = MultiIndex.from_tuples([("a", "b"), ("b", "c"), ("c", "a")])
result = mi == ("c", "a")
expected = np.array([False, False, True])
tm.assert_numpy_array_equal(result, expected)
result = mi == ("c",)
expected = np.array([False, False, False])
tm.assert_numpy_array_equal(result, expected)
def test_equals_multi(idx):
assert idx.equals(idx)
assert not idx.equals(idx.values)
assert idx.equals(Index(idx.values))
assert idx.equal_levels(idx)
assert not idx.equals(idx[:-1])
assert not idx.equals(idx[-1])
# different number of levels
index = MultiIndex(
levels=[Index(list(range(4))), Index(list(range(4))), Index(list(range(4)))],
codes=[
np.array([0, 0, 1, 2, 2, 2, 3, 3]),
np.array([0, 1, 0, 0, 0, 1, 0, 1]),
np.array([1, 0, 1, 1, 0, 0, 1, 0]),
],
)
index2 = MultiIndex(levels=index.levels[:-1], codes=index.codes[:-1])
assert not index.equals(index2)
assert not index.equal_levels(index2)
# levels are different
major_axis = Index(list(range(4)))
minor_axis = Index(list(range(2)))
major_codes = np.array([0, 0, 1, 2, 2, 3])
minor_codes = np.array([0, 1, 0, 0, 1, 0])
index = MultiIndex(
levels=[major_axis, minor_axis], codes=[major_codes, minor_codes]
)
assert not idx.equals(index)
assert not idx.equal_levels(index)
# some of the labels are different
major_axis = Index(["foo", "bar", "baz", "qux"])
minor_axis = Index(["one", "two"])
major_codes = np.array([0, 0, 2, 2, 3, 3])
minor_codes = np.array([0, 1, 0, 1, 0, 1])
index = MultiIndex(
levels=[major_axis, minor_axis], codes=[major_codes, minor_codes]
)
assert not idx.equals(index)
def test_identical(idx):
mi = idx.copy()
mi2 = idx.copy()
assert mi.identical(mi2)
mi = mi.set_names(["new1", "new2"])
assert mi.equals(mi2)
assert not mi.identical(mi2)
mi2 = mi2.set_names(["new1", "new2"])
assert mi.identical(mi2)
mi3 = Index(mi.tolist(), names=mi.names)
msg = r"Unexpected keyword arguments {'names'}"
with pytest.raises(TypeError, match=msg):
Index(mi.tolist(), names=mi.names, tupleize_cols=False)
mi4 = Index(mi.tolist(), tupleize_cols=False)
assert mi.identical(mi3)
assert not mi.identical(mi4)
assert mi.equals(mi4)
def test_equals_operator(idx):
# GH9785
assert (idx == idx).all()
def test_equals_missing_values():
# make sure take is not using -1
i = MultiIndex.from_tuples([(0, pd.NaT), (0, pd.Timestamp("20130101"))])
result = i[0:1].equals(i[0])
assert not result
result = i[1:2].equals(i[1])
assert not result
def test_is_():
mi = MultiIndex.from_tuples(zip(range(10), range(10)))
assert mi.is_(mi)
assert mi.is_(mi.view())
assert mi.is_(mi.view().view().view().view())
mi2 = mi.view()
# names are metadata, they don't change id
mi2.names = ["A", "B"]
assert mi2.is_(mi)
assert mi.is_(mi2)
assert not mi.is_(mi.set_names(["C", "D"]))
mi2 = mi.view()
mi2.set_names(["E", "F"], inplace=True)
assert mi.is_(mi2)
# levels are inherent properties, they change identity
mi3 = mi2.set_levels([list(range(10)), list(range(10))])
assert not mi3.is_(mi2)
# shouldn't change
assert mi2.is_(mi)
mi4 = mi3.view()
# GH 17464 - Remove duplicate MultiIndex levels
with tm.assert_produces_warning(FutureWarning):
mi4.set_levels([list(range(10)), list(range(10))], inplace=True)
assert not mi4.is_(mi3)
mi5 = mi.view()
with tm.assert_produces_warning(FutureWarning):
mi5.set_levels(mi5.levels, inplace=True)
assert not mi5.is_(mi)
def test_is_all_dates(idx):
assert not idx._is_all_dates
def test_is_numeric(idx):
# MultiIndex is never numeric
assert not idx.is_numeric()
def test_multiindex_compare():
# GH 21149
# Ensure comparison operations for MultiIndex with nlevels == 1
# behave consistently with those for MultiIndex with nlevels > 1
midx = MultiIndex.from_product([[0, 1]])
# Equality self-test: MultiIndex object vs self
expected = Series([True, True])
result = Series(midx == midx)
tm.assert_series_equal(result, expected)
# Greater than comparison: MultiIndex object vs self
expected = Series([False, False])
result = Series(midx > midx)
tm.assert_series_equal(result, expected)