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test_scalar_compat.py
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"""
Tests for DatetimeIndex methods behaving like their Timestamp counterparts
"""
from datetime import datetime
import numpy as np
import pytest
from pandas._libs.tslibs import (
OutOfBoundsDatetime,
to_offset,
)
from pandas._libs.tslibs.offsets import INVALID_FREQ_ERR_MSG
import pandas as pd
from pandas import (
DatetimeIndex,
Timestamp,
date_range,
)
import pandas._testing as tm
class TestDatetimeIndexOps:
def test_dti_time(self):
rng = date_range("1/1/2000", freq="12min", periods=10)
result = pd.Index(rng).time
expected = [t.time() for t in rng]
assert (result == expected).all()
def test_dti_date(self):
rng = date_range("1/1/2000", freq="12H", periods=10)
result = pd.Index(rng).date
expected = [t.date() for t in rng]
assert (result == expected).all()
@pytest.mark.parametrize("data", [["1400-01-01"], [datetime(1400, 1, 1)]])
def test_dti_date_out_of_range(self, data):
# GH#1475
msg = (
"^Out of bounds nanosecond timestamp: "
"1400-01-01( 00:00:00)?, at position 0$"
)
with pytest.raises(OutOfBoundsDatetime, match=msg):
DatetimeIndex(data)
@pytest.mark.parametrize(
"field",
[
"dayofweek",
"day_of_week",
"dayofyear",
"day_of_year",
"quarter",
"days_in_month",
"is_month_start",
"is_month_end",
"is_quarter_start",
"is_quarter_end",
"is_year_start",
"is_year_end",
],
)
def test_dti_timestamp_fields(self, field):
# extra fields from DatetimeIndex like quarter and week
idx = tm.makeDateIndex(100)
expected = getattr(idx, field)[-1]
result = getattr(Timestamp(idx[-1]), field)
assert result == expected
def test_dti_timestamp_isocalendar_fields(self):
idx = tm.makeDateIndex(100)
expected = tuple(idx.isocalendar().iloc[-1].to_list())
result = idx[-1].isocalendar()
assert result == expected
# ----------------------------------------------------------------
# DatetimeIndex.round
def test_round_daily(self):
dti = date_range("20130101 09:10:11", periods=5)
result = dti.round("D")
expected = date_range("20130101", periods=5)
tm.assert_index_equal(result, expected)
dti = dti.tz_localize("UTC").tz_convert("US/Eastern")
result = dti.round("D")
expected = date_range("20130101", periods=5).tz_localize("US/Eastern")
tm.assert_index_equal(result, expected)
result = dti.round("s")
tm.assert_index_equal(result, dti)
@pytest.mark.parametrize(
"freq, error_msg",
[
("Y", "<YearEnd: month=12> is a non-fixed frequency"),
("M", "<MonthEnd> is a non-fixed frequency"),
("foobar", "Invalid frequency: foobar"),
],
)
def test_round_invalid(self, freq, error_msg):
dti = date_range("20130101 09:10:11", periods=5)
dti = dti.tz_localize("UTC").tz_convert("US/Eastern")
with pytest.raises(ValueError, match=error_msg):
dti.round(freq)
def test_round(self, tz_naive_fixture):
tz = tz_naive_fixture
rng = date_range(start="2016-01-01", periods=5, freq="30Min", tz=tz)
elt = rng[1]
expected_rng = DatetimeIndex(
[
Timestamp("2016-01-01 00:00:00", tz=tz),
Timestamp("2016-01-01 00:00:00", tz=tz),
Timestamp("2016-01-01 01:00:00", tz=tz),
Timestamp("2016-01-01 02:00:00", tz=tz),
Timestamp("2016-01-01 02:00:00", tz=tz),
]
)
expected_elt = expected_rng[1]
tm.assert_index_equal(rng.round(freq="H"), expected_rng)
assert elt.round(freq="H") == expected_elt
msg = INVALID_FREQ_ERR_MSG
with pytest.raises(ValueError, match=msg):
rng.round(freq="foo")
with pytest.raises(ValueError, match=msg):
elt.round(freq="foo")
msg = "<MonthEnd> is a non-fixed frequency"
with pytest.raises(ValueError, match=msg):
rng.round(freq="M")
with pytest.raises(ValueError, match=msg):
elt.round(freq="M")
# GH#14440 & GH#15578
index = DatetimeIndex(["2016-10-17 12:00:00.0015"], tz=tz)
result = index.round("ms")
expected = DatetimeIndex(["2016-10-17 12:00:00.002000"], tz=tz)
tm.assert_index_equal(result, expected)
for freq in ["us", "ns"]:
tm.assert_index_equal(index, index.round(freq))
index = DatetimeIndex(["2016-10-17 12:00:00.00149"], tz=tz)
result = index.round("ms")
expected = DatetimeIndex(["2016-10-17 12:00:00.001000"], tz=tz)
tm.assert_index_equal(result, expected)
index = DatetimeIndex(["2016-10-17 12:00:00.001501031"])
result = index.round("10ns")
expected = DatetimeIndex(["2016-10-17 12:00:00.001501030"])
tm.assert_index_equal(result, expected)
with tm.assert_produces_warning(False):
ts = "2016-10-17 12:00:00.001501031"
DatetimeIndex([ts]).round("1010ns")
def test_no_rounding_occurs(self, tz_naive_fixture):
# GH 21262
tz = tz_naive_fixture
rng = date_range(start="2016-01-01", periods=5, freq="2Min", tz=tz)
expected_rng = DatetimeIndex(
[
Timestamp("2016-01-01 00:00:00", tz=tz),
Timestamp("2016-01-01 00:02:00", tz=tz),
Timestamp("2016-01-01 00:04:00", tz=tz),
Timestamp("2016-01-01 00:06:00", tz=tz),
Timestamp("2016-01-01 00:08:00", tz=tz),
]
)
tm.assert_index_equal(rng.round(freq="2T"), expected_rng)
@pytest.mark.parametrize(
"test_input, rounder, freq, expected",
[
(["2117-01-01 00:00:45"], "floor", "15s", ["2117-01-01 00:00:45"]),
(["2117-01-01 00:00:45"], "ceil", "15s", ["2117-01-01 00:00:45"]),
(
["2117-01-01 00:00:45.000000012"],
"floor",
"10ns",
["2117-01-01 00:00:45.000000010"],
),
(
["1823-01-01 00:00:01.000000012"],
"ceil",
"10ns",
["1823-01-01 00:00:01.000000020"],
),
(["1823-01-01 00:00:01"], "floor", "1s", ["1823-01-01 00:00:01"]),
(["1823-01-01 00:00:01"], "ceil", "1s", ["1823-01-01 00:00:01"]),
(["2018-01-01 00:15:00"], "ceil", "15T", ["2018-01-01 00:15:00"]),
(["2018-01-01 00:15:00"], "floor", "15T", ["2018-01-01 00:15:00"]),
(["1823-01-01 03:00:00"], "ceil", "3H", ["1823-01-01 03:00:00"]),
(["1823-01-01 03:00:00"], "floor", "3H", ["1823-01-01 03:00:00"]),
(
("NaT", "1823-01-01 00:00:01"),
"floor",
"1s",
("NaT", "1823-01-01 00:00:01"),
),
(
("NaT", "1823-01-01 00:00:01"),
"ceil",
"1s",
("NaT", "1823-01-01 00:00:01"),
),
],
)
def test_ceil_floor_edge(self, test_input, rounder, freq, expected):
dt = DatetimeIndex(list(test_input))
func = getattr(dt, rounder)
result = func(freq)
expected = DatetimeIndex(list(expected))
assert expected.equals(result)
@pytest.mark.parametrize(
"start, index_freq, periods",
[("2018-01-01", "12H", 25), ("2018-01-01 0:0:0.124999", "1ns", 1000)],
)
@pytest.mark.parametrize(
"round_freq",
[
"2ns",
"3ns",
"4ns",
"5ns",
"6ns",
"7ns",
"250ns",
"500ns",
"750ns",
"1us",
"19us",
"250us",
"500us",
"750us",
"1s",
"2s",
"3s",
"12H",
"1D",
],
)
def test_round_int64(self, start, index_freq, periods, round_freq):
dt = date_range(start=start, freq=index_freq, periods=periods)
unit = to_offset(round_freq).nanos
# test floor
result = dt.floor(round_freq)
diff = dt.asi8 - result.asi8
mod = result.asi8 % unit
assert (mod == 0).all(), f"floor not a {round_freq} multiple"
assert (0 <= diff).all() and (diff < unit).all(), "floor error"
# test ceil
result = dt.ceil(round_freq)
diff = result.asi8 - dt.asi8
mod = result.asi8 % unit
assert (mod == 0).all(), f"ceil not a {round_freq} multiple"
assert (0 <= diff).all() and (diff < unit).all(), "ceil error"
# test round
result = dt.round(round_freq)
diff = abs(result.asi8 - dt.asi8)
mod = result.asi8 % unit
assert (mod == 0).all(), f"round not a {round_freq} multiple"
assert (diff <= unit // 2).all(), "round error"
if unit % 2 == 0:
assert (
result.asi8[diff == unit // 2] % 2 == 0
).all(), "round half to even error"
# ----------------------------------------------------------------
# DatetimeIndex.normalize
def test_normalize(self):
rng = date_range("1/1/2000 9:30", periods=10, freq="D")
result = rng.normalize()
expected = date_range("1/1/2000", periods=10, freq="D")
tm.assert_index_equal(result, expected)
arr_ns = np.array([1380585623454345752, 1380585612343234312]).astype(
"datetime64[ns]"
)
rng_ns = DatetimeIndex(arr_ns)
rng_ns_normalized = rng_ns.normalize()
arr_ns = np.array([1380585600000000000, 1380585600000000000]).astype(
"datetime64[ns]"
)
expected = DatetimeIndex(arr_ns)
tm.assert_index_equal(rng_ns_normalized, expected)
assert result.is_normalized
assert not rng.is_normalized
def test_normalize_nat(self):
dti = DatetimeIndex([pd.NaT, Timestamp("2018-01-01 01:00:00")])
result = dti.normalize()
expected = DatetimeIndex([pd.NaT, Timestamp("2018-01-01")])
tm.assert_index_equal(result, expected)
class TestDateTimeIndexToJulianDate:
def test_1700(self):
dr = date_range(start=Timestamp("1710-10-01"), periods=5, freq="D")
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Index) and r2.dtype == np.float64
tm.assert_index_equal(r1, r2)
def test_2000(self):
dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="D")
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Index) and r2.dtype == np.float64
tm.assert_index_equal(r1, r2)
def test_hour(self):
dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="H")
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Index) and r2.dtype == np.float64
tm.assert_index_equal(r1, r2)
def test_minute(self):
dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="T")
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Index) and r2.dtype == np.float64
tm.assert_index_equal(r1, r2)
def test_second(self):
dr = date_range(start=Timestamp("2000-02-27"), periods=5, freq="S")
r1 = pd.Index([x.to_julian_date() for x in dr])
r2 = dr.to_julian_date()
assert isinstance(r2, pd.Index) and r2.dtype == np.float64
tm.assert_index_equal(r1, r2)