230 lines
8.2 KiB
Python
230 lines
8.2 KiB
Python
![]() |
from datetime import time, timedelta
|
||
|
|
||
|
import numpy as np
|
||
|
import pytest
|
||
|
|
||
|
import pandas as pd
|
||
|
from pandas import Series, TimedeltaIndex, isna, to_timedelta
|
||
|
import pandas._testing as tm
|
||
|
|
||
|
|
||
|
class TestTimedeltas:
|
||
|
@pytest.mark.parametrize("readonly", [True, False])
|
||
|
def test_to_timedelta_readonly(self, readonly):
|
||
|
# GH#34857
|
||
|
arr = np.array([], dtype=object)
|
||
|
if readonly:
|
||
|
arr.setflags(write=False)
|
||
|
result = to_timedelta(arr)
|
||
|
expected = to_timedelta([])
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
def test_to_timedelta(self):
|
||
|
|
||
|
result = to_timedelta(["", ""])
|
||
|
assert isna(result).all()
|
||
|
|
||
|
# pass thru
|
||
|
result = to_timedelta(np.array([np.timedelta64(1, "s")]))
|
||
|
expected = pd.Index(np.array([np.timedelta64(1, "s")]))
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
# Series
|
||
|
expected = Series([timedelta(days=1), timedelta(days=1, seconds=1)])
|
||
|
result = to_timedelta(Series(["1d", "1days 00:00:01"]))
|
||
|
tm.assert_series_equal(result, expected)
|
||
|
|
||
|
# with units
|
||
|
result = TimedeltaIndex(
|
||
|
[np.timedelta64(0, "ns"), np.timedelta64(10, "s").astype("m8[ns]")]
|
||
|
)
|
||
|
expected = to_timedelta([0, 10], unit="s")
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
# arrays of various dtypes
|
||
|
arr = np.array([1] * 5, dtype="int64")
|
||
|
result = to_timedelta(arr, unit="s")
|
||
|
expected = TimedeltaIndex([np.timedelta64(1, "s")] * 5)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
arr = np.array([1] * 5, dtype="int64")
|
||
|
result = to_timedelta(arr, unit="m")
|
||
|
expected = TimedeltaIndex([np.timedelta64(1, "m")] * 5)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
arr = np.array([1] * 5, dtype="int64")
|
||
|
result = to_timedelta(arr, unit="h")
|
||
|
expected = TimedeltaIndex([np.timedelta64(1, "h")] * 5)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
arr = np.array([1] * 5, dtype="timedelta64[s]")
|
||
|
result = to_timedelta(arr)
|
||
|
expected = TimedeltaIndex([np.timedelta64(1, "s")] * 5)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
arr = np.array([1] * 5, dtype="timedelta64[D]")
|
||
|
result = to_timedelta(arr)
|
||
|
expected = TimedeltaIndex([np.timedelta64(1, "D")] * 5)
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
def test_to_timedelta_dataframe(self):
|
||
|
# GH 11776
|
||
|
arr = np.arange(10).reshape(2, 5)
|
||
|
df = pd.DataFrame(np.arange(10).reshape(2, 5))
|
||
|
for arg in (arr, df):
|
||
|
with pytest.raises(TypeError, match="1-d array"):
|
||
|
to_timedelta(arg)
|
||
|
for errors in ["ignore", "raise", "coerce"]:
|
||
|
with pytest.raises(TypeError, match="1-d array"):
|
||
|
to_timedelta(arg, errors=errors)
|
||
|
|
||
|
def test_to_timedelta_invalid(self):
|
||
|
|
||
|
# bad value for errors parameter
|
||
|
msg = "errors must be one of"
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
to_timedelta(["foo"], errors="never")
|
||
|
|
||
|
# these will error
|
||
|
msg = "invalid unit abbreviation: foo"
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
to_timedelta([1, 2], unit="foo")
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
to_timedelta(1, unit="foo")
|
||
|
|
||
|
# time not supported ATM
|
||
|
msg = (
|
||
|
"Value must be Timedelta, string, integer, float, timedelta or convertible"
|
||
|
)
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
to_timedelta(time(second=1))
|
||
|
assert to_timedelta(time(second=1), errors="coerce") is pd.NaT
|
||
|
|
||
|
msg = "unit abbreviation w/o a number"
|
||
|
with pytest.raises(ValueError, match=msg):
|
||
|
to_timedelta(["foo", "bar"])
|
||
|
tm.assert_index_equal(
|
||
|
TimedeltaIndex([pd.NaT, pd.NaT]),
|
||
|
to_timedelta(["foo", "bar"], errors="coerce"),
|
||
|
)
|
||
|
|
||
|
tm.assert_index_equal(
|
||
|
TimedeltaIndex(["1 day", pd.NaT, "1 min"]),
|
||
|
to_timedelta(["1 day", "bar", "1 min"], errors="coerce"),
|
||
|
)
|
||
|
|
||
|
# gh-13613: these should not error because errors='ignore'
|
||
|
invalid_data = "apple"
|
||
|
assert invalid_data == to_timedelta(invalid_data, errors="ignore")
|
||
|
|
||
|
invalid_data = ["apple", "1 days"]
|
||
|
tm.assert_numpy_array_equal(
|
||
|
np.array(invalid_data, dtype=object),
|
||
|
to_timedelta(invalid_data, errors="ignore"),
|
||
|
)
|
||
|
|
||
|
invalid_data = pd.Index(["apple", "1 days"])
|
||
|
tm.assert_index_equal(invalid_data, to_timedelta(invalid_data, errors="ignore"))
|
||
|
|
||
|
invalid_data = Series(["apple", "1 days"])
|
||
|
tm.assert_series_equal(
|
||
|
invalid_data, to_timedelta(invalid_data, errors="ignore")
|
||
|
)
|
||
|
|
||
|
@pytest.mark.parametrize(
|
||
|
"val, warning",
|
||
|
[
|
||
|
("1M", FutureWarning),
|
||
|
("1 M", FutureWarning),
|
||
|
("1Y", FutureWarning),
|
||
|
("1 Y", FutureWarning),
|
||
|
("1y", FutureWarning),
|
||
|
("1 y", FutureWarning),
|
||
|
("1m", None),
|
||
|
("1 m", None),
|
||
|
("1 day", None),
|
||
|
("2day", None),
|
||
|
],
|
||
|
)
|
||
|
def test_unambiguous_timedelta_values(self, val, warning):
|
||
|
# GH36666 Deprecate use of strings denoting units with 'M', 'Y', 'm' or 'y'
|
||
|
# in pd.to_timedelta
|
||
|
with tm.assert_produces_warning(warning, check_stacklevel=False):
|
||
|
to_timedelta(val)
|
||
|
|
||
|
def test_to_timedelta_via_apply(self):
|
||
|
# GH 5458
|
||
|
expected = Series([np.timedelta64(1, "s")])
|
||
|
result = Series(["00:00:01"]).apply(to_timedelta)
|
||
|
tm.assert_series_equal(result, expected)
|
||
|
|
||
|
result = Series([to_timedelta("00:00:01")])
|
||
|
tm.assert_series_equal(result, expected)
|
||
|
|
||
|
def test_to_timedelta_on_missing_values(self):
|
||
|
# GH5438
|
||
|
timedelta_NaT = np.timedelta64("NaT")
|
||
|
|
||
|
actual = pd.to_timedelta(Series(["00:00:01", np.nan]))
|
||
|
expected = Series(
|
||
|
[np.timedelta64(1000000000, "ns"), timedelta_NaT], dtype="<m8[ns]"
|
||
|
)
|
||
|
tm.assert_series_equal(actual, expected)
|
||
|
|
||
|
actual = pd.to_timedelta(Series(["00:00:01", pd.NaT]))
|
||
|
tm.assert_series_equal(actual, expected)
|
||
|
|
||
|
actual = pd.to_timedelta(np.nan)
|
||
|
assert actual.value == timedelta_NaT.astype("int64")
|
||
|
|
||
|
actual = pd.to_timedelta(pd.NaT)
|
||
|
assert actual.value == timedelta_NaT.astype("int64")
|
||
|
|
||
|
def test_to_timedelta_float(self):
|
||
|
# https://github.com/pandas-dev/pandas/issues/25077
|
||
|
arr = np.arange(0, 1, 1e-6)[-10:]
|
||
|
result = pd.to_timedelta(arr, unit="s")
|
||
|
expected_asi8 = np.arange(999990000, int(1e9), 1000, dtype="int64")
|
||
|
tm.assert_numpy_array_equal(result.asi8, expected_asi8)
|
||
|
|
||
|
def test_to_timedelta_coerce_strings_unit(self):
|
||
|
arr = np.array([1, 2, "error"], dtype=object)
|
||
|
result = pd.to_timedelta(arr, unit="ns", errors="coerce")
|
||
|
expected = pd.to_timedelta([1, 2, pd.NaT], unit="ns")
|
||
|
tm.assert_index_equal(result, expected)
|
||
|
|
||
|
def test_to_timedelta_ignore_strings_unit(self):
|
||
|
arr = np.array([1, 2, "error"], dtype=object)
|
||
|
result = pd.to_timedelta(arr, unit="ns", errors="ignore")
|
||
|
tm.assert_numpy_array_equal(result, arr)
|
||
|
|
||
|
def test_to_timedelta_nullable_int64_dtype(self):
|
||
|
# GH 35574
|
||
|
expected = Series([timedelta(days=1), timedelta(days=2)])
|
||
|
result = to_timedelta(Series([1, 2], dtype="Int64"), unit="days")
|
||
|
|
||
|
tm.assert_series_equal(result, expected)
|
||
|
|
||
|
# IntegerArray Series with nulls
|
||
|
expected = Series([timedelta(days=1), None])
|
||
|
result = to_timedelta(Series([1, None], dtype="Int64"), unit="days")
|
||
|
|
||
|
tm.assert_series_equal(result, expected)
|
||
|
|
||
|
@pytest.mark.parametrize(
|
||
|
("input", "expected"),
|
||
|
[
|
||
|
("8:53:08.71800000001", "8:53:08.718"),
|
||
|
("8:53:08.718001", "8:53:08.718001"),
|
||
|
("8:53:08.7180000001", "8:53:08.7180000001"),
|
||
|
("-8:53:08.71800000001", "-8:53:08.718"),
|
||
|
("8:53:08.7180000089", "8:53:08.718000008"),
|
||
|
],
|
||
|
)
|
||
|
@pytest.mark.parametrize("func", [pd.Timedelta, pd.to_timedelta])
|
||
|
def test_to_timedelta_precision_over_nanos(self, input, expected, func):
|
||
|
# GH: 36738
|
||
|
expected = pd.Timedelta(expected)
|
||
|
result = func(input)
|
||
|
assert result == expected
|