169 lines
5.6 KiB
Python
169 lines
5.6 KiB
Python
from datetime import date
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import dateutil
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import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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DataFrame,
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DatetimeIndex,
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Index,
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Timestamp,
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date_range,
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offsets,
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)
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import pandas._testing as tm
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class TestDatetimeIndex:
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def test_time_overflow_for_32bit_machines(self):
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# GH8943. On some machines NumPy defaults to np.int32 (for example,
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# 32-bit Linux machines). In the function _generate_regular_range
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# found in tseries/index.py, `periods` gets multiplied by `strides`
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# (which has value 1e9) and since the max value for np.int32 is ~2e9,
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# and since those machines won't promote np.int32 to np.int64, we get
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# overflow.
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periods = np.int_(1000)
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idx1 = date_range(start="2000", periods=periods, freq="S")
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assert len(idx1) == periods
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idx2 = date_range(end="2000", periods=periods, freq="S")
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assert len(idx2) == periods
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def test_nat(self):
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assert DatetimeIndex([np.nan])[0] is pd.NaT
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def test_week_of_month_frequency(self):
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# GH 5348: "ValueError: Could not evaluate WOM-1SUN" shouldn't raise
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d1 = date(2002, 9, 1)
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d2 = date(2013, 10, 27)
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d3 = date(2012, 9, 30)
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idx1 = DatetimeIndex([d1, d2])
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idx2 = DatetimeIndex([d3])
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result_append = idx1.append(idx2)
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expected = DatetimeIndex([d1, d2, d3])
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tm.assert_index_equal(result_append, expected)
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result_union = idx1.union(idx2)
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expected = DatetimeIndex([d1, d3, d2])
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tm.assert_index_equal(result_union, expected)
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# GH 5115
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result = date_range("2013-1-1", periods=4, freq="WOM-1SAT")
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dates = ["2013-01-05", "2013-02-02", "2013-03-02", "2013-04-06"]
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expected = DatetimeIndex(dates, freq="WOM-1SAT")
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tm.assert_index_equal(result, expected)
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def test_append_nondatetimeindex(self):
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rng = date_range("1/1/2000", periods=10)
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idx = Index(["a", "b", "c", "d"])
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result = rng.append(idx)
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assert isinstance(result[0], Timestamp)
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def test_iteration_preserves_tz(self):
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# see gh-8890
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index = date_range("2012-01-01", periods=3, freq="H", tz="US/Eastern")
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for i, ts in enumerate(index):
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result = ts
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expected = index[i]
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assert result == expected
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index = date_range(
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"2012-01-01", periods=3, freq="H", tz=dateutil.tz.tzoffset(None, -28800)
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)
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for i, ts in enumerate(index):
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result = ts
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expected = index[i]
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assert result._repr_base == expected._repr_base
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assert result == expected
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# 9100
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index = DatetimeIndex(
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["2014-12-01 03:32:39.987000-08:00", "2014-12-01 04:12:34.987000-08:00"]
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)
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for i, ts in enumerate(index):
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result = ts
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expected = index[i]
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assert result._repr_base == expected._repr_base
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assert result == expected
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@pytest.mark.parametrize("periods", [0, 9999, 10000, 10001])
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def test_iteration_over_chunksize(self, periods):
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# GH21012
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index = date_range("2000-01-01 00:00:00", periods=periods, freq="min")
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num = 0
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for stamp in index:
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assert index[num] == stamp
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num += 1
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assert num == len(index)
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def test_misc_coverage(self):
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rng = date_range("1/1/2000", periods=5)
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result = rng.groupby(rng.day)
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assert isinstance(list(result.values())[0][0], Timestamp)
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def test_groupby_function_tuple_1677(self):
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df = DataFrame(np.random.rand(100), index=date_range("1/1/2000", periods=100))
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monthly_group = df.groupby(lambda x: (x.year, x.month))
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result = monthly_group.mean()
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assert isinstance(result.index[0], tuple)
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def assert_index_parameters(self, index):
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assert index.freq == "40960N"
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assert index.inferred_freq == "40960N"
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def test_ns_index(self):
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nsamples = 400
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ns = int(1e9 / 24414)
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dtstart = np.datetime64("2012-09-20T00:00:00")
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dt = dtstart + np.arange(nsamples) * np.timedelta64(ns, "ns")
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freq = ns * offsets.Nano()
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index = DatetimeIndex(dt, freq=freq, name="time")
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self.assert_index_parameters(index)
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new_index = date_range(start=index[0], end=index[-1], freq=index.freq)
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self.assert_index_parameters(new_index)
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def test_asarray_tz_naive(self):
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# This shouldn't produce a warning.
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idx = date_range("2000", periods=2)
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# M8[ns] by default
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result = np.asarray(idx)
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expected = np.array(["2000-01-01", "2000-01-02"], dtype="M8[ns]")
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tm.assert_numpy_array_equal(result, expected)
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# optionally, object
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result = np.asarray(idx, dtype=object)
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expected = np.array([Timestamp("2000-01-01"), Timestamp("2000-01-02")])
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tm.assert_numpy_array_equal(result, expected)
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def test_asarray_tz_aware(self):
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tz = "US/Central"
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idx = date_range("2000", periods=2, tz=tz)
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expected = np.array(["2000-01-01T06", "2000-01-02T06"], dtype="M8[ns]")
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result = np.asarray(idx, dtype="datetime64[ns]")
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tm.assert_numpy_array_equal(result, expected)
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# Old behavior with no warning
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result = np.asarray(idx, dtype="M8[ns]")
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tm.assert_numpy_array_equal(result, expected)
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# Future behavior with no warning
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expected = np.array(
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[Timestamp("2000-01-01", tz=tz), Timestamp("2000-01-02", tz=tz)]
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)
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result = np.asarray(idx, dtype=object)
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tm.assert_numpy_array_equal(result, expected)
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