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168 lines
6 KiB
Python
168 lines
6 KiB
Python
"""
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Tests for DataFrame timezone-related methods
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"""
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import numpy as np
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import pytest
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import pytz
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from pandas.core.dtypes.dtypes import DatetimeTZDtype
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import pandas as pd
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from pandas import DataFrame, Series
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import pandas._testing as tm
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from pandas.core.indexes.datetimes import date_range
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class TestDataFrameTimezones:
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def test_frame_values_with_tz(self):
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tz = "US/Central"
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df = DataFrame({"A": date_range("2000", periods=4, tz=tz)})
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result = df.values
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expected = np.array(
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[
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[pd.Timestamp("2000-01-01", tz=tz)],
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[pd.Timestamp("2000-01-02", tz=tz)],
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[pd.Timestamp("2000-01-03", tz=tz)],
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[pd.Timestamp("2000-01-04", tz=tz)],
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]
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)
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tm.assert_numpy_array_equal(result, expected)
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# two columns, homogenous
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df = df.assign(B=df.A)
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result = df.values
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expected = np.concatenate([expected, expected], axis=1)
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tm.assert_numpy_array_equal(result, expected)
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# three columns, heterogeneous
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est = "US/Eastern"
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df = df.assign(C=df.A.dt.tz_convert(est))
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new = np.array(
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[
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[pd.Timestamp("2000-01-01T01:00:00", tz=est)],
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[pd.Timestamp("2000-01-02T01:00:00", tz=est)],
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[pd.Timestamp("2000-01-03T01:00:00", tz=est)],
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[pd.Timestamp("2000-01-04T01:00:00", tz=est)],
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]
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)
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expected = np.concatenate([expected, new], axis=1)
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result = df.values
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tm.assert_numpy_array_equal(result, expected)
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def test_frame_join_tzaware(self):
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test1 = DataFrame(
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np.zeros((6, 3)),
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index=date_range(
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"2012-11-15 00:00:00", periods=6, freq="100L", tz="US/Central"
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),
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)
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test2 = DataFrame(
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np.zeros((3, 3)),
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index=date_range(
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"2012-11-15 00:00:00", periods=3, freq="250L", tz="US/Central"
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),
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columns=range(3, 6),
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)
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result = test1.join(test2, how="outer")
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ex_index = test1.index.union(test2.index)
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tm.assert_index_equal(result.index, ex_index)
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assert result.index.tz.zone == "US/Central"
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def test_frame_align_aware(self):
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idx1 = date_range("2001", periods=5, freq="H", tz="US/Eastern")
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idx2 = date_range("2001", periods=5, freq="2H", tz="US/Eastern")
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df1 = DataFrame(np.random.randn(len(idx1), 3), idx1)
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df2 = DataFrame(np.random.randn(len(idx2), 3), idx2)
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new1, new2 = df1.align(df2)
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assert df1.index.tz == new1.index.tz
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assert df2.index.tz == new2.index.tz
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# different timezones convert to UTC
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# frame with frame
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df1_central = df1.tz_convert("US/Central")
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new1, new2 = df1.align(df1_central)
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assert new1.index.tz == pytz.UTC
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assert new2.index.tz == pytz.UTC
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# frame with Series
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new1, new2 = df1.align(df1_central[0], axis=0)
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assert new1.index.tz == pytz.UTC
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assert new2.index.tz == pytz.UTC
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df1[0].align(df1_central, axis=0)
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assert new1.index.tz == pytz.UTC
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assert new2.index.tz == pytz.UTC
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@pytest.mark.parametrize("tz", ["US/Eastern", "dateutil/US/Eastern"])
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def test_frame_no_datetime64_dtype(self, tz):
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# after GH#7822
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# these retain the timezones on dict construction
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dr = date_range("2011/1/1", "2012/1/1", freq="W-FRI")
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dr_tz = dr.tz_localize(tz)
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df = DataFrame({"A": "foo", "B": dr_tz}, index=dr)
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tz_expected = DatetimeTZDtype("ns", dr_tz.tzinfo)
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assert df["B"].dtype == tz_expected
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# GH#2810 (with timezones)
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datetimes_naive = [ts.to_pydatetime() for ts in dr]
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datetimes_with_tz = [ts.to_pydatetime() for ts in dr_tz]
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df = DataFrame({"dr": dr})
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df["dr_tz"] = dr_tz
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df["datetimes_naive"] = datetimes_naive
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df["datetimes_with_tz"] = datetimes_with_tz
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result = df.dtypes
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expected = Series(
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[
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np.dtype("datetime64[ns]"),
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DatetimeTZDtype(tz=tz),
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np.dtype("datetime64[ns]"),
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DatetimeTZDtype(tz=tz),
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],
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index=["dr", "dr_tz", "datetimes_naive", "datetimes_with_tz"],
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)
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize("tz", ["US/Eastern", "dateutil/US/Eastern"])
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def test_frame_reset_index(self, tz):
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dr = date_range("2012-06-02", periods=10, tz=tz)
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df = DataFrame(np.random.randn(len(dr)), dr)
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roundtripped = df.reset_index().set_index("index")
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xp = df.index.tz
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rs = roundtripped.index.tz
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assert xp == rs
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@pytest.mark.parametrize("tz", [None, "America/New_York"])
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def test_boolean_compare_transpose_tzindex_with_dst(self, tz):
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# GH 19970
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idx = date_range("20161101", "20161130", freq="4H", tz=tz)
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df = DataFrame({"a": range(len(idx)), "b": range(len(idx))}, index=idx)
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result = df.T == df.T
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expected = DataFrame(True, index=list("ab"), columns=idx)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.parametrize("copy", [True, False])
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@pytest.mark.parametrize(
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"method, tz", [["tz_localize", None], ["tz_convert", "Europe/Berlin"]]
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)
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def test_tz_localize_convert_copy_inplace_mutate(self, copy, method, tz):
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# GH 6326
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result = DataFrame(
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np.arange(0, 5), index=date_range("20131027", periods=5, freq="1H", tz=tz)
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)
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getattr(result, method)("UTC", copy=copy)
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expected = DataFrame(
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np.arange(0, 5), index=date_range("20131027", periods=5, freq="1H", tz=tz)
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)
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tm.assert_frame_equal(result, expected)
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def test_constructor_data_aware_dtype_naive(self, tz_aware_fixture):
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# GH 25843
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tz = tz_aware_fixture
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result = DataFrame({"d": [pd.Timestamp("2019", tz=tz)]}, dtype="datetime64[ns]")
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expected = DataFrame({"d": [pd.Timestamp("2019")]})
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tm.assert_frame_equal(result, expected)
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