""" Tests for the Index constructor conducting inference. """ from decimal import Decimal import numpy as np import pytest from pandas.core.dtypes.common import is_unsigned_integer_dtype from pandas import ( NA, Categorical, CategoricalIndex, DatetimeIndex, Index, Int64Index, IntervalIndex, MultiIndex, NaT, PeriodIndex, Series, TimedeltaIndex, Timestamp, UInt64Index, date_range, period_range, timedelta_range, ) import pandas._testing as tm class TestIndexConstructorInference: @pytest.mark.parametrize("na_value", [None, np.nan]) @pytest.mark.parametrize("vtype", [list, tuple, iter]) def test_construction_list_tuples_nan(self, na_value, vtype): # GH#18505 : valid tuples containing NaN values = [(1, "two"), (3.0, na_value)] result = Index(vtype(values)) expected = MultiIndex.from_tuples(values) tm.assert_index_equal(result, expected) @pytest.mark.parametrize( "dtype", [int, "int64", "int32", "int16", "int8", "uint64", "uint32", "uint16", "uint8"], ) def test_constructor_int_dtype_float(self, dtype): # GH#18400 if is_unsigned_integer_dtype(dtype): index_type = UInt64Index else: index_type = Int64Index expected = index_type([0, 1, 2, 3]) result = Index([0.0, 1.0, 2.0, 3.0], dtype=dtype) tm.assert_index_equal(result, expected) @pytest.mark.parametrize("cast_index", [True, False]) @pytest.mark.parametrize( "vals", [[True, False, True], np.array([True, False, True], dtype=bool)] ) def test_constructor_dtypes_to_object(self, cast_index, vals): if cast_index: index = Index(vals, dtype=bool) else: index = Index(vals) assert type(index) is Index assert index.dtype == object def test_constructor_categorical_to_object(self): # GH#32167 Categorical data and dtype=object should return object-dtype ci = CategoricalIndex(range(5)) result = Index(ci, dtype=object) assert not isinstance(result, CategoricalIndex) def test_constructor_infer_periodindex(self): xp = period_range("2012-1-1", freq="M", periods=3) rs = Index(xp) tm.assert_index_equal(rs, xp) assert isinstance(rs, PeriodIndex) def test_from_list_of_periods(self): rng = period_range("1/1/2000", periods=20, freq="D") periods = list(rng) result = Index(periods) assert isinstance(result, PeriodIndex) @pytest.mark.parametrize("pos", [0, 1]) @pytest.mark.parametrize( "klass,dtype,ctor", [ (DatetimeIndex, "datetime64[ns]", np.datetime64("nat")), (TimedeltaIndex, "timedelta64[ns]", np.timedelta64("nat")), ], ) def test_constructor_infer_nat_dt_like( self, pos, klass, dtype, ctor, nulls_fixture, request ): if isinstance(nulls_fixture, Decimal): # We dont cast these to datetime64/timedelta64 return expected = klass([NaT, NaT]) assert expected.dtype == dtype data = [ctor] data.insert(pos, nulls_fixture) warn = None if nulls_fixture is NA: expected = Index([NA, NaT]) mark = pytest.mark.xfail(reason="Broken with np.NaT ctor; see GH 31884") request.node.add_marker(mark) # GH#35942 numpy will emit a DeprecationWarning within the # assert_index_equal calls. Since we can't do anything # about it until GH#31884 is fixed, we suppress that warning. warn = DeprecationWarning result = Index(data) with tm.assert_produces_warning(warn): tm.assert_index_equal(result, expected) result = Index(np.array(data, dtype=object)) with tm.assert_produces_warning(warn): tm.assert_index_equal(result, expected) @pytest.mark.parametrize("swap_objs", [True, False]) def test_constructor_mixed_nat_objs_infers_object(self, swap_objs): # mixed np.datetime64/timedelta64 nat results in object data = [np.datetime64("nat"), np.timedelta64("nat")] if swap_objs: data = data[::-1] expected = Index(data, dtype=object) tm.assert_index_equal(Index(data), expected) tm.assert_index_equal(Index(np.array(data, dtype=object)), expected) @pytest.mark.parametrize("swap_objs", [True, False]) def test_constructor_datetime_and_datetime64(self, swap_objs): data = [Timestamp(2021, 6, 8, 9, 42), np.datetime64("now")] if swap_objs: data = data[::-1] expected = DatetimeIndex(data) tm.assert_index_equal(Index(data), expected) tm.assert_index_equal(Index(np.array(data, dtype=object)), expected) class TestDtypeEnforced: # check we don't silently ignore the dtype keyword @pytest.mark.parametrize("dtype", [object, "float64", "uint64", "category"]) def test_constructor_range_values_mismatched_dtype(self, dtype): rng = Index(range(5)) result = Index(rng, dtype=dtype) assert result.dtype == dtype result = Index(range(5), dtype=dtype) assert result.dtype == dtype @pytest.mark.parametrize("dtype", [object, "float64", "uint64", "category"]) def test_constructor_categorical_values_mismatched_non_ea_dtype(self, dtype): cat = Categorical([1, 2, 3]) result = Index(cat, dtype=dtype) assert result.dtype == dtype def test_constructor_categorical_values_mismatched_dtype(self): dti = date_range("2016-01-01", periods=3) cat = Categorical(dti) result = Index(cat, dti.dtype) tm.assert_index_equal(result, dti) dti2 = dti.tz_localize("Asia/Tokyo") cat2 = Categorical(dti2) result = Index(cat2, dti2.dtype) tm.assert_index_equal(result, dti2) ii = IntervalIndex.from_breaks(range(5)) cat3 = Categorical(ii) result = Index(cat3, dtype=ii.dtype) tm.assert_index_equal(result, ii) def test_constructor_ea_values_mismatched_categorical_dtype(self): dti = date_range("2016-01-01", periods=3) result = Index(dti, dtype="category") expected = CategoricalIndex(dti) tm.assert_index_equal(result, expected) dti2 = date_range("2016-01-01", periods=3, tz="US/Pacific") result = Index(dti2, dtype="category") expected = CategoricalIndex(dti2) tm.assert_index_equal(result, expected) def test_constructor_period_values_mismatched_dtype(self): pi = period_range("2016-01-01", periods=3, freq="D") result = Index(pi, dtype="category") expected = CategoricalIndex(pi) tm.assert_index_equal(result, expected) def test_constructor_timedelta64_values_mismatched_dtype(self): # check we don't silently ignore the dtype keyword tdi = timedelta_range("4 Days", periods=5) result = Index(tdi, dtype="category") expected = CategoricalIndex(tdi) tm.assert_index_equal(result, expected) def test_constructor_interval_values_mismatched_dtype(self): dti = date_range("2016-01-01", periods=3) ii = IntervalIndex.from_breaks(dti) result = Index(ii, dtype="category") expected = CategoricalIndex(ii) tm.assert_index_equal(result, expected) def test_constructor_datetime64_values_mismatched_period_dtype(self): dti = date_range("2016-01-01", periods=3) result = Index(dti, dtype="Period[D]") expected = dti.to_period("D") tm.assert_index_equal(result, expected) class TestIndexConstructorUnwrapping: # Test passing different arraylike values to pd.Index @pytest.mark.parametrize("klass", [Index, DatetimeIndex]) def test_constructor_from_series_dt64(self, klass): stamps = [Timestamp("20110101"), Timestamp("20120101"), Timestamp("20130101")] expected = DatetimeIndex(stamps) ser = Series(stamps) result = klass(ser) tm.assert_index_equal(result, expected)