126 lines
4.0 KiB
Python
126 lines
4.0 KiB
Python
|
from datetime import timedelta
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
import pytest
|
||
|
|
|
||
|
|
import pandas as pd
|
||
|
|
from pandas import (
|
||
|
|
Float64Index,
|
||
|
|
Index,
|
||
|
|
Int64Index,
|
||
|
|
NaT,
|
||
|
|
Timedelta,
|
||
|
|
TimedeltaIndex,
|
||
|
|
timedelta_range,
|
||
|
|
)
|
||
|
|
import pandas._testing as tm
|
||
|
|
|
||
|
|
|
||
|
|
class TestTimedeltaIndex:
|
||
|
|
def test_astype_object(self):
|
||
|
|
idx = timedelta_range(start="1 days", periods=4, freq="D", name="idx")
|
||
|
|
expected_list = [
|
||
|
|
Timedelta("1 days"),
|
||
|
|
Timedelta("2 days"),
|
||
|
|
Timedelta("3 days"),
|
||
|
|
Timedelta("4 days"),
|
||
|
|
]
|
||
|
|
result = idx.astype(object)
|
||
|
|
expected = Index(expected_list, dtype=object, name="idx")
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
assert idx.tolist() == expected_list
|
||
|
|
|
||
|
|
def test_astype_object_with_nat(self):
|
||
|
|
idx = TimedeltaIndex(
|
||
|
|
[timedelta(days=1), timedelta(days=2), NaT, timedelta(days=4)], name="idx"
|
||
|
|
)
|
||
|
|
expected_list = [
|
||
|
|
Timedelta("1 days"),
|
||
|
|
Timedelta("2 days"),
|
||
|
|
NaT,
|
||
|
|
Timedelta("4 days"),
|
||
|
|
]
|
||
|
|
result = idx.astype(object)
|
||
|
|
expected = Index(expected_list, dtype=object, name="idx")
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
assert idx.tolist() == expected_list
|
||
|
|
|
||
|
|
def test_astype(self):
|
||
|
|
# GH 13149, GH 13209
|
||
|
|
idx = TimedeltaIndex([1e14, "NaT", NaT, np.NaN], name="idx")
|
||
|
|
|
||
|
|
result = idx.astype(object)
|
||
|
|
expected = Index(
|
||
|
|
[Timedelta("1 days 03:46:40")] + [NaT] * 3, dtype=object, name="idx"
|
||
|
|
)
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
result = idx.astype(int)
|
||
|
|
expected = Int64Index(
|
||
|
|
[100000000000000] + [-9223372036854775808] * 3, dtype=np.int64, name="idx"
|
||
|
|
)
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
result = idx.astype(str)
|
||
|
|
expected = Index([str(x) for x in idx], name="idx")
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
rng = timedelta_range("1 days", periods=10)
|
||
|
|
result = rng.astype("i8")
|
||
|
|
tm.assert_index_equal(result, Index(rng.asi8))
|
||
|
|
tm.assert_numpy_array_equal(rng.asi8, result.values)
|
||
|
|
|
||
|
|
def test_astype_uint(self):
|
||
|
|
arr = timedelta_range("1H", periods=2)
|
||
|
|
expected = pd.UInt64Index(
|
||
|
|
np.array([3600000000000, 90000000000000], dtype="uint64")
|
||
|
|
)
|
||
|
|
|
||
|
|
tm.assert_index_equal(arr.astype("uint64"), expected)
|
||
|
|
tm.assert_index_equal(arr.astype("uint32"), expected)
|
||
|
|
|
||
|
|
def test_astype_timedelta64(self):
|
||
|
|
# GH 13149, GH 13209
|
||
|
|
idx = TimedeltaIndex([1e14, "NaT", NaT, np.NaN])
|
||
|
|
|
||
|
|
result = idx.astype("timedelta64")
|
||
|
|
expected = Float64Index([1e14] + [np.NaN] * 3, dtype="float64")
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
result = idx.astype("timedelta64[ns]")
|
||
|
|
tm.assert_index_equal(result, idx)
|
||
|
|
assert result is not idx
|
||
|
|
|
||
|
|
result = idx.astype("timedelta64[ns]", copy=False)
|
||
|
|
tm.assert_index_equal(result, idx)
|
||
|
|
assert result is idx
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("dtype", [float, "datetime64", "datetime64[ns]"])
|
||
|
|
def test_astype_raises(self, dtype):
|
||
|
|
# GH 13149, GH 13209
|
||
|
|
idx = TimedeltaIndex([1e14, "NaT", NaT, np.NaN])
|
||
|
|
msg = "Cannot cast TimedeltaArray to dtype"
|
||
|
|
with pytest.raises(TypeError, match=msg):
|
||
|
|
idx.astype(dtype)
|
||
|
|
|
||
|
|
def test_astype_category(self):
|
||
|
|
obj = timedelta_range("1H", periods=2, freq="H")
|
||
|
|
|
||
|
|
result = obj.astype("category")
|
||
|
|
expected = pd.CategoricalIndex([Timedelta("1H"), Timedelta("2H")])
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
result = obj._data.astype("category")
|
||
|
|
expected = expected.values
|
||
|
|
tm.assert_categorical_equal(result, expected)
|
||
|
|
|
||
|
|
def test_astype_array_fallback(self):
|
||
|
|
obj = timedelta_range("1H", periods=2)
|
||
|
|
result = obj.astype(bool)
|
||
|
|
expected = Index(np.array([True, True]))
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
result = obj._data.astype(bool)
|
||
|
|
expected = np.array([True, True])
|
||
|
|
tm.assert_numpy_array_equal(result, expected)
|