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- import numpy as np
- import pytest
- from pandas.core.dtypes.common import ensure_platform_int
- import pandas as pd
- from pandas import (
- Index,
- RangeIndex,
- )
- import pandas._testing as tm
- from pandas.tests.indexes.common import NumericBase
- # aliases to make some tests easier to read
- RI = RangeIndex
- class TestRangeIndex(NumericBase):
- _index_cls = RangeIndex
- @pytest.fixture
- def dtype(self):
- return np.int64
- @pytest.fixture(
- params=["uint64", "float64", "category", "datetime64", "object"],
- )
- def invalid_dtype(self, request):
- return request.param
- @pytest.fixture
- def simple_index(self):
- return self._index_cls(start=0, stop=20, step=2)
- @pytest.fixture(
- params=[
- RangeIndex(start=0, stop=20, step=2, name="foo"),
- RangeIndex(start=18, stop=-1, step=-2, name="bar"),
- ],
- ids=["index_inc", "index_dec"],
- )
- def index(self, request):
- return request.param
- def test_constructor_unwraps_index(self, dtype):
- result = self._index_cls(1, 3)
- expected = np.array([1, 2], dtype=dtype)
- tm.assert_numpy_array_equal(result._data, expected)
- def test_can_hold_identifiers(self, simple_index):
- idx = simple_index
- key = idx[0]
- assert idx._can_hold_identifiers_and_holds_name(key) is False
- def test_too_many_names(self, simple_index):
- index = simple_index
- with pytest.raises(ValueError, match="^Length"):
- index.names = ["roger", "harold"]
- @pytest.mark.parametrize(
- "index, start, stop, step",
- [
- (RangeIndex(5), 0, 5, 1),
- (RangeIndex(0, 5), 0, 5, 1),
- (RangeIndex(5, step=2), 0, 5, 2),
- (RangeIndex(1, 5, 2), 1, 5, 2),
- ],
- )
- def test_start_stop_step_attrs(self, index, start, stop, step):
- # GH 25710
- assert index.start == start
- assert index.stop == stop
- assert index.step == step
- def test_copy(self):
- i = RangeIndex(5, name="Foo")
- i_copy = i.copy()
- assert i_copy is not i
- assert i_copy.identical(i)
- assert i_copy._range == range(0, 5, 1)
- assert i_copy.name == "Foo"
- def test_repr(self):
- i = RangeIndex(5, name="Foo")
- result = repr(i)
- expected = "RangeIndex(start=0, stop=5, step=1, name='Foo')"
- assert result == expected
- result = eval(result)
- tm.assert_index_equal(result, i, exact=True)
- i = RangeIndex(5, 0, -1)
- result = repr(i)
- expected = "RangeIndex(start=5, stop=0, step=-1)"
- assert result == expected
- result = eval(result)
- tm.assert_index_equal(result, i, exact=True)
- def test_insert(self):
- idx = RangeIndex(5, name="Foo")
- result = idx[1:4]
- # test 0th element
- tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]), exact="equiv")
- # GH 18295 (test missing)
- expected = Index([0, np.nan, 1, 2, 3, 4], dtype=np.float64)
- for na in [np.nan, None, pd.NA]:
- result = RangeIndex(5).insert(1, na)
- tm.assert_index_equal(result, expected)
- result = RangeIndex(5).insert(1, pd.NaT)
- expected = Index([0, pd.NaT, 1, 2, 3, 4], dtype=object)
- tm.assert_index_equal(result, expected)
- def test_insert_edges_preserves_rangeindex(self):
- idx = Index(range(4, 9, 2))
- result = idx.insert(0, 2)
- expected = Index(range(2, 9, 2))
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.insert(3, 10)
- expected = Index(range(4, 11, 2))
- tm.assert_index_equal(result, expected, exact=True)
- def test_insert_middle_preserves_rangeindex(self):
- # insert in the middle
- idx = Index(range(0, 3, 2))
- result = idx.insert(1, 1)
- expected = Index(range(3))
- tm.assert_index_equal(result, expected, exact=True)
- idx = idx * 2
- result = idx.insert(1, 2)
- expected = expected * 2
- tm.assert_index_equal(result, expected, exact=True)
- def test_delete(self):
- idx = RangeIndex(5, name="Foo")
- expected = idx[1:]
- result = idx.delete(0)
- tm.assert_index_equal(result, expected, exact=True)
- assert result.name == expected.name
- expected = idx[:-1]
- result = idx.delete(-1)
- tm.assert_index_equal(result, expected, exact=True)
- assert result.name == expected.name
- msg = "index 5 is out of bounds for axis 0 with size 5"
- with pytest.raises((IndexError, ValueError), match=msg):
- # either depending on numpy version
- result = idx.delete(len(idx))
- def test_delete_preserves_rangeindex(self):
- idx = Index(range(2), name="foo")
- result = idx.delete([1])
- expected = Index(range(1), name="foo")
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.delete(1)
- tm.assert_index_equal(result, expected, exact=True)
- def test_delete_preserves_rangeindex_middle(self):
- idx = Index(range(3), name="foo")
- result = idx.delete(1)
- expected = idx[::2]
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.delete(-2)
- tm.assert_index_equal(result, expected, exact=True)
- def test_delete_preserves_rangeindex_list_at_end(self):
- idx = RangeIndex(0, 6, 1)
- loc = [2, 3, 4, 5]
- result = idx.delete(loc)
- expected = idx[:2]
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.delete(loc[::-1])
- tm.assert_index_equal(result, expected, exact=True)
- def test_delete_preserves_rangeindex_list_middle(self):
- idx = RangeIndex(0, 6, 1)
- loc = [1, 2, 3, 4]
- result = idx.delete(loc)
- expected = RangeIndex(0, 6, 5)
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.delete(loc[::-1])
- tm.assert_index_equal(result, expected, exact=True)
- def test_delete_all_preserves_rangeindex(self):
- idx = RangeIndex(0, 6, 1)
- loc = [0, 1, 2, 3, 4, 5]
- result = idx.delete(loc)
- expected = idx[:0]
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.delete(loc[::-1])
- tm.assert_index_equal(result, expected, exact=True)
- def test_delete_not_preserving_rangeindex(self):
- idx = RangeIndex(0, 6, 1)
- loc = [0, 3, 5]
- result = idx.delete(loc)
- expected = Index([1, 2, 4])
- tm.assert_index_equal(result, expected, exact=True)
- result = idx.delete(loc[::-1])
- tm.assert_index_equal(result, expected, exact=True)
- def test_view(self):
- i = RangeIndex(0, name="Foo")
- i_view = i.view()
- assert i_view.name == "Foo"
- i_view = i.view("i8")
- tm.assert_numpy_array_equal(i.values, i_view)
- i_view = i.view(RangeIndex)
- tm.assert_index_equal(i, i_view)
- def test_dtype(self, simple_index):
- index = simple_index
- assert index.dtype == np.int64
- def test_cache(self):
- # GH 26565, GH26617, GH35432
- # This test checks whether _cache has been set.
- # Calling RangeIndex._cache["_data"] creates an int64 array of the same length
- # as the RangeIndex and stores it in _cache.
- idx = RangeIndex(0, 100, 10)
- assert idx._cache == {}
- repr(idx)
- assert idx._cache == {}
- str(idx)
- assert idx._cache == {}
- idx.get_loc(20)
- assert idx._cache == {}
- 90 in idx # True
- assert idx._cache == {}
- 91 in idx # False
- assert idx._cache == {}
- idx.all()
- assert idx._cache == {}
- idx.any()
- assert idx._cache == {}
- for _ in idx:
- pass
- assert idx._cache == {}
- idx.format()
- assert idx._cache == {}
- df = pd.DataFrame({"a": range(10)}, index=idx)
- str(df)
- assert idx._cache == {}
- df.loc[50]
- assert idx._cache == {}
- with pytest.raises(KeyError, match="51"):
- df.loc[51]
- assert idx._cache == {}
- df.loc[10:50]
- assert idx._cache == {}
- df.iloc[5:10]
- assert idx._cache == {}
- # idx._cache should contain a _data entry after call to idx._data
- idx._data
- assert isinstance(idx._data, np.ndarray)
- assert idx._data is idx._data # check cached value is reused
- assert len(idx._cache) == 1
- expected = np.arange(0, 100, 10, dtype="int64")
- tm.assert_numpy_array_equal(idx._cache["_data"], expected)
- def test_is_monotonic(self):
- index = RangeIndex(0, 20, 2)
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is False
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is False
- index = RangeIndex(4, 0, -1)
- assert index.is_monotonic_increasing is False
- assert index._is_strictly_monotonic_increasing is False
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_decreasing is True
- index = RangeIndex(1, 2)
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is True
- index = RangeIndex(2, 1)
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is True
- index = RangeIndex(1, 1)
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_increasing is True
- assert index.is_monotonic_decreasing is True
- assert index._is_strictly_monotonic_increasing is True
- assert index._is_strictly_monotonic_decreasing is True
- def test_equals_range(self):
- equiv_pairs = [
- (RangeIndex(0, 9, 2), RangeIndex(0, 10, 2)),
- (RangeIndex(0), RangeIndex(1, -1, 3)),
- (RangeIndex(1, 2, 3), RangeIndex(1, 3, 4)),
- (RangeIndex(0, -9, -2), RangeIndex(0, -10, -2)),
- ]
- for left, right in equiv_pairs:
- assert left.equals(right)
- assert right.equals(left)
- def test_logical_compat(self, simple_index):
- idx = simple_index
- assert idx.all() == idx.values.all()
- assert idx.any() == idx.values.any()
- def test_identical(self, simple_index):
- index = simple_index
- i = Index(index.copy())
- assert i.identical(index)
- # we don't allow object dtype for RangeIndex
- if isinstance(index, RangeIndex):
- return
- same_values_different_type = Index(i, dtype=object)
- assert not i.identical(same_values_different_type)
- i = index.copy(dtype=object)
- i = i.rename("foo")
- same_values = Index(i, dtype=object)
- assert same_values.identical(index.copy(dtype=object))
- assert not i.identical(index)
- assert Index(same_values, name="foo", dtype=object).identical(i)
- assert not index.copy(dtype=object).identical(index.copy(dtype="int64"))
- def test_nbytes(self):
- # memory savings vs int index
- idx = RangeIndex(0, 1000)
- assert idx.nbytes < Index(idx._values).nbytes / 10
- # constant memory usage
- i2 = RangeIndex(0, 10)
- assert idx.nbytes == i2.nbytes
- @pytest.mark.parametrize(
- "start,stop,step",
- [
- # can't
- ("foo", "bar", "baz"),
- # shouldn't
- ("0", "1", "2"),
- ],
- )
- def test_cant_or_shouldnt_cast(self, start, stop, step):
- msg = f"Wrong type {type(start)} for value {start}"
- with pytest.raises(TypeError, match=msg):
- RangeIndex(start, stop, step)
- def test_view_index(self, simple_index):
- index = simple_index
- index.view(Index)
- def test_prevent_casting(self, simple_index):
- index = simple_index
- result = index.astype("O")
- assert result.dtype == np.object_
- def test_repr_roundtrip(self, simple_index):
- index = simple_index
- tm.assert_index_equal(eval(repr(index)), index)
- def test_slice_keep_name(self):
- idx = RangeIndex(1, 2, name="asdf")
- assert idx.name == idx[1:].name
- def test_has_duplicates(self, index):
- assert index.is_unique
- assert not index.has_duplicates
- def test_extended_gcd(self, simple_index):
- index = simple_index
- result = index._extended_gcd(6, 10)
- assert result[0] == result[1] * 6 + result[2] * 10
- assert 2 == result[0]
- result = index._extended_gcd(10, 6)
- assert 2 == result[1] * 10 + result[2] * 6
- assert 2 == result[0]
- def test_min_fitting_element(self):
- result = RangeIndex(0, 20, 2)._min_fitting_element(1)
- assert 2 == result
- result = RangeIndex(1, 6)._min_fitting_element(1)
- assert 1 == result
- result = RangeIndex(18, -2, -2)._min_fitting_element(1)
- assert 2 == result
- result = RangeIndex(5, 0, -1)._min_fitting_element(1)
- assert 1 == result
- big_num = 500000000000000000000000
- result = RangeIndex(5, big_num * 2, 1)._min_fitting_element(big_num)
- assert big_num == result
- def test_pickle_compat_construction(self):
- # RangeIndex() is a valid constructor
- pass
- def test_slice_specialised(self, simple_index):
- index = simple_index
- index.name = "foo"
- # scalar indexing
- res = index[1]
- expected = 2
- assert res == expected
- res = index[-1]
- expected = 18
- assert res == expected
- # slicing
- # slice value completion
- index_slice = index[:]
- expected = index
- tm.assert_index_equal(index_slice, expected)
- # positive slice values
- index_slice = index[7:10:2]
- expected = Index([14, 18], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- # negative slice values
- index_slice = index[-1:-5:-2]
- expected = Index([18, 14], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- # stop overshoot
- index_slice = index[2:100:4]
- expected = Index([4, 12], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- # reverse
- index_slice = index[::-1]
- expected = Index(index.values[::-1], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- index_slice = index[-8::-1]
- expected = Index([4, 2, 0], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- index_slice = index[-40::-1]
- expected = Index(np.array([], dtype=np.int64), name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- index_slice = index[40::-1]
- expected = Index(index.values[40::-1], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- index_slice = index[10::-1]
- expected = Index(index.values[::-1], name="foo")
- tm.assert_index_equal(index_slice, expected, exact="equiv")
- @pytest.mark.parametrize("step", set(range(-5, 6)) - {0})
- def test_len_specialised(self, step):
- # make sure that our len is the same as np.arange calc
- start, stop = (0, 5) if step > 0 else (5, 0)
- arr = np.arange(start, stop, step)
- index = RangeIndex(start, stop, step)
- assert len(index) == len(arr)
- index = RangeIndex(stop, start, step)
- assert len(index) == 0
- @pytest.fixture(
- params=[
- ([RI(1, 12, 5)], RI(1, 12, 5)),
- ([RI(0, 6, 4)], RI(0, 6, 4)),
- ([RI(1, 3), RI(3, 7)], RI(1, 7)),
- ([RI(1, 5, 2), RI(5, 6)], RI(1, 6, 2)),
- ([RI(1, 3, 2), RI(4, 7, 3)], RI(1, 7, 3)),
- ([RI(-4, 3, 2), RI(4, 7, 2)], RI(-4, 7, 2)),
- ([RI(-4, -8), RI(-8, -12)], RI(0, 0)),
- ([RI(-4, -8), RI(3, -4)], RI(0, 0)),
- ([RI(-4, -8), RI(3, 5)], RI(3, 5)),
- ([RI(-4, -2), RI(3, 5)], Index([-4, -3, 3, 4])),
- ([RI(-2), RI(3, 5)], RI(3, 5)),
- ([RI(2), RI(2)], Index([0, 1, 0, 1])),
- ([RI(2), RI(2, 5), RI(5, 8, 4)], RI(0, 6)),
- ([RI(2), RI(3, 5), RI(5, 8, 4)], Index([0, 1, 3, 4, 5])),
- ([RI(-2, 2), RI(2, 5), RI(5, 8, 4)], RI(-2, 6)),
- ([RI(3), Index([-1, 3, 15])], Index([0, 1, 2, -1, 3, 15])),
- ([RI(3), Index([-1, 3.1, 15.0])], Index([0, 1, 2, -1, 3.1, 15.0])),
- ([RI(3), Index(["a", None, 14])], Index([0, 1, 2, "a", None, 14])),
- ([RI(3, 1), Index(["a", None, 14])], Index(["a", None, 14])),
- ]
- )
- def appends(self, request):
- """Inputs and expected outputs for RangeIndex.append test"""
- return request.param
- def test_append(self, appends):
- # GH16212
- indices, expected = appends
- result = indices[0].append(indices[1:])
- tm.assert_index_equal(result, expected, exact=True)
- if len(indices) == 2:
- # Append single item rather than list
- result2 = indices[0].append(indices[1])
- tm.assert_index_equal(result2, expected, exact=True)
- def test_engineless_lookup(self):
- # GH 16685
- # Standard lookup on RangeIndex should not require the engine to be
- # created
- idx = RangeIndex(2, 10, 3)
- assert idx.get_loc(5) == 1
- tm.assert_numpy_array_equal(
- idx.get_indexer([2, 8]), ensure_platform_int(np.array([0, 2]))
- )
- with pytest.raises(KeyError, match="3"):
- idx.get_loc(3)
- assert "_engine" not in idx._cache
- # Different types of scalars can be excluded immediately, no need to
- # use the _engine
- with pytest.raises(KeyError, match="'a'"):
- idx.get_loc("a")
- assert "_engine" not in idx._cache
- def test_format_empty(self):
- # GH35712
- empty_idx = self._index_cls(0)
- assert empty_idx.format() == []
- assert empty_idx.format(name=True) == [""]
- @pytest.mark.parametrize(
- "RI",
- [
- RangeIndex(0, -1, -1),
- RangeIndex(0, 1, 1),
- RangeIndex(1, 3, 2),
- RangeIndex(0, -1, -2),
- RangeIndex(-3, -5, -2),
- ],
- )
- def test_append_len_one(self, RI):
- # GH39401
- result = RI.append([])
- tm.assert_index_equal(result, RI, exact=True)
- @pytest.mark.parametrize("base", [RangeIndex(0, 2), Index([0, 1])])
- def test_isin_range(self, base):
- # GH#41151
- values = RangeIndex(0, 1)
- result = base.isin(values)
- expected = np.array([True, False])
- tm.assert_numpy_array_equal(result, expected)
- def test_sort_values_key(self):
- # GH#43666
- sort_order = {8: 2, 6: 0, 4: 8, 2: 10, 0: 12}
- values = RangeIndex(0, 10, 2)
- result = values.sort_values(key=lambda x: x.map(sort_order))
- expected = Index([4, 8, 6, 0, 2], dtype="int64")
- tm.assert_index_equal(result, expected, check_exact=True)
- def test_cast_string(self, dtype):
- pytest.skip("casting of strings not relevant for RangeIndex")
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