615 lines
18 KiB
Python
615 lines
18 KiB
Python
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"""
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Also test support for datetime64[ns] in Series / DataFrame
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"""
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from datetime import datetime, timedelta
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import re
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from dateutil.tz import gettz, tzutc
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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._libs import iNaT, index as libindex
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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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NaT,
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Series,
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Timestamp,
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date_range,
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period_range,
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)
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import pandas._testing as tm
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def test_fancy_getitem():
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dti = date_range(
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freq="WOM-1FRI", start=datetime(2005, 1, 1), end=datetime(2010, 1, 1)
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)
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s = Series(np.arange(len(dti)), index=dti)
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assert s[48] == 48
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assert s["1/2/2009"] == 48
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assert s["2009-1-2"] == 48
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assert s[datetime(2009, 1, 2)] == 48
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assert s[Timestamp(datetime(2009, 1, 2))] == 48
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with pytest.raises(KeyError, match=r"^'2009-1-3'$"):
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s["2009-1-3"]
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tm.assert_series_equal(
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s["3/6/2009":"2009-06-05"], s[datetime(2009, 3, 6) : datetime(2009, 6, 5)]
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)
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def test_fancy_setitem():
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dti = date_range(
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freq="WOM-1FRI", start=datetime(2005, 1, 1), end=datetime(2010, 1, 1)
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)
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s = Series(np.arange(len(dti)), index=dti)
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s[48] = -1
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assert s[48] == -1
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s["1/2/2009"] = -2
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assert s[48] == -2
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s["1/2/2009":"2009-06-05"] = -3
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assert (s[48:54] == -3).all()
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def test_slicing_datetimes():
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# GH 7523
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# unique
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df = DataFrame(
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np.arange(4.0, dtype="float64"),
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index=[datetime(2001, 1, i, 10, 00) for i in [1, 2, 3, 4]],
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)
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result = df.loc[datetime(2001, 1, 1, 10) :]
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tm.assert_frame_equal(result, df)
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result = df.loc[: datetime(2001, 1, 4, 10)]
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tm.assert_frame_equal(result, df)
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result = df.loc[datetime(2001, 1, 1, 10) : datetime(2001, 1, 4, 10)]
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tm.assert_frame_equal(result, df)
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result = df.loc[datetime(2001, 1, 1, 11) :]
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expected = df.iloc[1:]
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tm.assert_frame_equal(result, expected)
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result = df.loc["20010101 11":]
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tm.assert_frame_equal(result, expected)
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# duplicates
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df = DataFrame(
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np.arange(5.0, dtype="float64"),
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index=[datetime(2001, 1, i, 10, 00) for i in [1, 2, 2, 3, 4]],
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)
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result = df.loc[datetime(2001, 1, 1, 10) :]
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tm.assert_frame_equal(result, df)
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result = df.loc[: datetime(2001, 1, 4, 10)]
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tm.assert_frame_equal(result, df)
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result = df.loc[datetime(2001, 1, 1, 10) : datetime(2001, 1, 4, 10)]
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tm.assert_frame_equal(result, df)
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result = df.loc[datetime(2001, 1, 1, 11) :]
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expected = df.iloc[1:]
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tm.assert_frame_equal(result, expected)
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result = df.loc["20010101 11":]
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tm.assert_frame_equal(result, expected)
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def test_getitem_setitem_datetime_tz_pytz():
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N = 50
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# testing with timezone, GH #2785
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rng = date_range("1/1/1990", periods=N, freq="H", tz="US/Eastern")
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ts = Series(np.random.randn(N), index=rng)
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# also test Timestamp tz handling, GH #2789
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result = ts.copy()
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result["1990-01-01 09:00:00+00:00"] = 0
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result["1990-01-01 09:00:00+00:00"] = ts[4]
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tm.assert_series_equal(result, ts)
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result = ts.copy()
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result["1990-01-01 03:00:00-06:00"] = 0
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result["1990-01-01 03:00:00-06:00"] = ts[4]
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tm.assert_series_equal(result, ts)
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# repeat with datetimes
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result = ts.copy()
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result[datetime(1990, 1, 1, 9, tzinfo=pytz.timezone("UTC"))] = 0
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result[datetime(1990, 1, 1, 9, tzinfo=pytz.timezone("UTC"))] = ts[4]
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tm.assert_series_equal(result, ts)
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result = ts.copy()
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# comparison dates with datetime MUST be localized!
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date = pytz.timezone("US/Central").localize(datetime(1990, 1, 1, 3))
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result[date] = 0
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result[date] = ts[4]
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tm.assert_series_equal(result, ts)
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def test_getitem_setitem_datetime_tz_dateutil():
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tz = (
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lambda x: tzutc() if x == "UTC" else gettz(x)
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) # handle special case for utc in dateutil
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N = 50
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# testing with timezone, GH #2785
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rng = date_range("1/1/1990", periods=N, freq="H", tz="America/New_York")
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ts = Series(np.random.randn(N), index=rng)
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# also test Timestamp tz handling, GH #2789
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result = ts.copy()
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result["1990-01-01 09:00:00+00:00"] = 0
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result["1990-01-01 09:00:00+00:00"] = ts[4]
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tm.assert_series_equal(result, ts)
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result = ts.copy()
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result["1990-01-01 03:00:00-06:00"] = 0
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result["1990-01-01 03:00:00-06:00"] = ts[4]
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tm.assert_series_equal(result, ts)
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# repeat with datetimes
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result = ts.copy()
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result[datetime(1990, 1, 1, 9, tzinfo=tz("UTC"))] = 0
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result[datetime(1990, 1, 1, 9, tzinfo=tz("UTC"))] = ts[4]
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tm.assert_series_equal(result, ts)
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result = ts.copy()
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result[datetime(1990, 1, 1, 3, tzinfo=tz("America/Chicago"))] = 0
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result[datetime(1990, 1, 1, 3, tzinfo=tz("America/Chicago"))] = ts[4]
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tm.assert_series_equal(result, ts)
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def test_getitem_setitem_datetimeindex():
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N = 50
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# testing with timezone, GH #2785
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rng = date_range("1/1/1990", periods=N, freq="H", tz="US/Eastern")
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ts = Series(np.random.randn(N), index=rng)
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result = ts["1990-01-01 04:00:00"]
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expected = ts[4]
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assert result == expected
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result = ts.copy()
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result["1990-01-01 04:00:00"] = 0
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result["1990-01-01 04:00:00"] = ts[4]
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tm.assert_series_equal(result, ts)
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result = ts["1990-01-01 04:00:00":"1990-01-01 07:00:00"]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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result = ts.copy()
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result["1990-01-01 04:00:00":"1990-01-01 07:00:00"] = 0
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result["1990-01-01 04:00:00":"1990-01-01 07:00:00"] = ts[4:8]
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tm.assert_series_equal(result, ts)
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lb = "1990-01-01 04:00:00"
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rb = "1990-01-01 07:00:00"
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# GH#18435 strings get a pass from tzawareness compat
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result = ts[(ts.index >= lb) & (ts.index <= rb)]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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lb = "1990-01-01 04:00:00-0500"
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rb = "1990-01-01 07:00:00-0500"
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result = ts[(ts.index >= lb) & (ts.index <= rb)]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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# But we do not give datetimes a pass on tzawareness compat
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# TODO: do the same with Timestamps and dt64
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msg = "Cannot compare tz-naive and tz-aware datetime-like objects"
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naive = datetime(1990, 1, 1, 4)
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with tm.assert_produces_warning(FutureWarning):
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# GH#36148 will require tzawareness compat
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result = ts[naive]
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expected = ts[4]
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assert result == expected
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result = ts.copy()
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with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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# GH#36148 will require tzawareness compat
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result[datetime(1990, 1, 1, 4)] = 0
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with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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# GH#36148 will require tzawareness compat
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result[datetime(1990, 1, 1, 4)] = ts[4]
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tm.assert_series_equal(result, ts)
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with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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# GH#36148 will require tzawareness compat
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result = ts[datetime(1990, 1, 1, 4) : datetime(1990, 1, 1, 7)]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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result = ts.copy()
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with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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# GH#36148 will require tzawareness compat
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result[datetime(1990, 1, 1, 4) : datetime(1990, 1, 1, 7)] = 0
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with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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# GH#36148 will require tzawareness compat
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result[datetime(1990, 1, 1, 4) : datetime(1990, 1, 1, 7)] = ts[4:8]
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tm.assert_series_equal(result, ts)
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lb = datetime(1990, 1, 1, 4)
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rb = datetime(1990, 1, 1, 7)
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msg = r"Invalid comparison between dtype=datetime64\[ns, US/Eastern\] and datetime"
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with pytest.raises(TypeError, match=msg):
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# tznaive vs tzaware comparison is invalid
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# see GH#18376, GH#18162
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ts[(ts.index >= lb) & (ts.index <= rb)]
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lb = Timestamp(datetime(1990, 1, 1, 4)).tz_localize(rng.tzinfo)
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rb = Timestamp(datetime(1990, 1, 1, 7)).tz_localize(rng.tzinfo)
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result = ts[(ts.index >= lb) & (ts.index <= rb)]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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result = ts[ts.index[4]]
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expected = ts[4]
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assert result == expected
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result = ts[ts.index[4:8]]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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result = ts.copy()
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result[ts.index[4:8]] = 0
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result.iloc[4:8] = ts.iloc[4:8]
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tm.assert_series_equal(result, ts)
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# also test partial date slicing
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result = ts["1990-01-02"]
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expected = ts[24:48]
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tm.assert_series_equal(result, expected)
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result = ts.copy()
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result["1990-01-02"] = 0
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result["1990-01-02"] = ts[24:48]
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tm.assert_series_equal(result, ts)
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def test_getitem_setitem_periodindex():
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N = 50
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rng = period_range("1/1/1990", periods=N, freq="H")
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ts = Series(np.random.randn(N), index=rng)
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result = ts["1990-01-01 04"]
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expected = ts[4]
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assert result == expected
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result = ts.copy()
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result["1990-01-01 04"] = 0
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result["1990-01-01 04"] = ts[4]
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tm.assert_series_equal(result, ts)
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result = ts["1990-01-01 04":"1990-01-01 07"]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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result = ts.copy()
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result["1990-01-01 04":"1990-01-01 07"] = 0
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result["1990-01-01 04":"1990-01-01 07"] = ts[4:8]
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tm.assert_series_equal(result, ts)
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lb = "1990-01-01 04"
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rb = "1990-01-01 07"
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result = ts[(ts.index >= lb) & (ts.index <= rb)]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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# GH 2782
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result = ts[ts.index[4]]
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expected = ts[4]
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assert result == expected
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result = ts[ts.index[4:8]]
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expected = ts[4:8]
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tm.assert_series_equal(result, expected)
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result = ts.copy()
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result[ts.index[4:8]] = 0
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result.iloc[4:8] = ts.iloc[4:8]
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tm.assert_series_equal(result, ts)
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def test_datetime_indexing():
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index = date_range("1/1/2000", "1/7/2000")
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index = index.repeat(3)
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s = Series(len(index), index=index)
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stamp = Timestamp("1/8/2000")
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with pytest.raises(KeyError, match=re.escape(repr(stamp))):
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s[stamp]
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s[stamp] = 0
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assert s[stamp] == 0
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# not monotonic
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s = Series(len(index), index=index)
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s = s[::-1]
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with pytest.raises(KeyError, match=re.escape(repr(stamp))):
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s[stamp]
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s[stamp] = 0
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assert s[stamp] == 0
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"""
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test duplicates in time series
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"""
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@pytest.fixture
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def dups():
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dates = [
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|
|
datetime(2000, 1, 2),
|
||
|
|
datetime(2000, 1, 2),
|
||
|
|
datetime(2000, 1, 2),
|
||
|
|
datetime(2000, 1, 3),
|
||
|
|
datetime(2000, 1, 3),
|
||
|
|
datetime(2000, 1, 3),
|
||
|
|
datetime(2000, 1, 4),
|
||
|
|
datetime(2000, 1, 4),
|
||
|
|
datetime(2000, 1, 4),
|
||
|
|
datetime(2000, 1, 5),
|
||
|
|
]
|
||
|
|
|
||
|
|
return Series(np.random.randn(len(dates)), index=dates)
|
||
|
|
|
||
|
|
|
||
|
|
def test_constructor(dups):
|
||
|
|
assert isinstance(dups, Series)
|
||
|
|
assert isinstance(dups.index, DatetimeIndex)
|
||
|
|
|
||
|
|
|
||
|
|
def test_is_unique_monotonic(dups):
|
||
|
|
assert not dups.index.is_unique
|
||
|
|
|
||
|
|
|
||
|
|
def test_index_unique(dups):
|
||
|
|
uniques = dups.index.unique()
|
||
|
|
expected = DatetimeIndex(
|
||
|
|
[
|
||
|
|
datetime(2000, 1, 2),
|
||
|
|
datetime(2000, 1, 3),
|
||
|
|
datetime(2000, 1, 4),
|
||
|
|
datetime(2000, 1, 5),
|
||
|
|
]
|
||
|
|
)
|
||
|
|
assert uniques.dtype == "M8[ns]" # sanity
|
||
|
|
tm.assert_index_equal(uniques, expected)
|
||
|
|
assert dups.index.nunique() == 4
|
||
|
|
|
||
|
|
# #2563
|
||
|
|
assert isinstance(uniques, DatetimeIndex)
|
||
|
|
|
||
|
|
dups_local = dups.index.tz_localize("US/Eastern")
|
||
|
|
dups_local.name = "foo"
|
||
|
|
result = dups_local.unique()
|
||
|
|
expected = DatetimeIndex(expected, name="foo")
|
||
|
|
expected = expected.tz_localize("US/Eastern")
|
||
|
|
assert result.tz is not None
|
||
|
|
assert result.name == "foo"
|
||
|
|
tm.assert_index_equal(result, expected)
|
||
|
|
|
||
|
|
# NaT, note this is excluded
|
||
|
|
arr = [1370745748 + t for t in range(20)] + [iNaT]
|
||
|
|
idx = DatetimeIndex(arr * 3)
|
||
|
|
tm.assert_index_equal(idx.unique(), DatetimeIndex(arr))
|
||
|
|
assert idx.nunique() == 20
|
||
|
|
assert idx.nunique(dropna=False) == 21
|
||
|
|
|
||
|
|
arr = [
|
||
|
|
Timestamp("2013-06-09 02:42:28") + timedelta(seconds=t) for t in range(20)
|
||
|
|
] + [NaT]
|
||
|
|
idx = DatetimeIndex(arr * 3)
|
||
|
|
tm.assert_index_equal(idx.unique(), DatetimeIndex(arr))
|
||
|
|
assert idx.nunique() == 20
|
||
|
|
assert idx.nunique(dropna=False) == 21
|
||
|
|
|
||
|
|
|
||
|
|
def test_duplicate_dates_indexing(dups):
|
||
|
|
ts = dups
|
||
|
|
|
||
|
|
uniques = ts.index.unique()
|
||
|
|
for date in uniques:
|
||
|
|
result = ts[date]
|
||
|
|
|
||
|
|
mask = ts.index == date
|
||
|
|
total = (ts.index == date).sum()
|
||
|
|
expected = ts[mask]
|
||
|
|
if total > 1:
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
else:
|
||
|
|
tm.assert_almost_equal(result, expected[0])
|
||
|
|
|
||
|
|
cp = ts.copy()
|
||
|
|
cp[date] = 0
|
||
|
|
expected = Series(np.where(mask, 0, ts), index=ts.index)
|
||
|
|
tm.assert_series_equal(cp, expected)
|
||
|
|
|
||
|
|
key = datetime(2000, 1, 6)
|
||
|
|
with pytest.raises(KeyError, match=re.escape(repr(key))):
|
||
|
|
ts[key]
|
||
|
|
|
||
|
|
# new index
|
||
|
|
ts[datetime(2000, 1, 6)] = 0
|
||
|
|
assert ts[datetime(2000, 1, 6)] == 0
|
||
|
|
|
||
|
|
|
||
|
|
def test_groupby_average_dup_values(dups):
|
||
|
|
result = dups.groupby(level=0).mean()
|
||
|
|
expected = dups.groupby(dups.index).mean()
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
|
||
|
|
def test_indexing_over_size_cutoff(monkeypatch):
|
||
|
|
# #1821
|
||
|
|
|
||
|
|
monkeypatch.setattr(libindex, "_SIZE_CUTOFF", 1000)
|
||
|
|
|
||
|
|
# create large list of non periodic datetime
|
||
|
|
dates = []
|
||
|
|
sec = timedelta(seconds=1)
|
||
|
|
half_sec = timedelta(microseconds=500000)
|
||
|
|
d = datetime(2011, 12, 5, 20, 30)
|
||
|
|
n = 1100
|
||
|
|
for i in range(n):
|
||
|
|
dates.append(d)
|
||
|
|
dates.append(d + sec)
|
||
|
|
dates.append(d + sec + half_sec)
|
||
|
|
dates.append(d + sec + sec + half_sec)
|
||
|
|
d += 3 * sec
|
||
|
|
|
||
|
|
# duplicate some values in the list
|
||
|
|
duplicate_positions = np.random.randint(0, len(dates) - 1, 20)
|
||
|
|
for p in duplicate_positions:
|
||
|
|
dates[p + 1] = dates[p]
|
||
|
|
|
||
|
|
df = DataFrame(np.random.randn(len(dates), 4), index=dates, columns=list("ABCD"))
|
||
|
|
|
||
|
|
pos = n * 3
|
||
|
|
timestamp = df.index[pos]
|
||
|
|
assert timestamp in df.index
|
||
|
|
|
||
|
|
# it works!
|
||
|
|
df.loc[timestamp]
|
||
|
|
assert len(df.loc[[timestamp]]) > 0
|
||
|
|
|
||
|
|
|
||
|
|
def test_indexing_over_size_cutoff_period_index(monkeypatch):
|
||
|
|
# GH 27136
|
||
|
|
|
||
|
|
monkeypatch.setattr(libindex, "_SIZE_CUTOFF", 1000)
|
||
|
|
|
||
|
|
n = 1100
|
||
|
|
idx = pd.period_range("1/1/2000", freq="T", periods=n)
|
||
|
|
assert idx._engine.over_size_threshold
|
||
|
|
|
||
|
|
s = Series(np.random.randn(len(idx)), index=idx)
|
||
|
|
|
||
|
|
pos = n - 1
|
||
|
|
timestamp = idx[pos]
|
||
|
|
assert timestamp in s.index
|
||
|
|
|
||
|
|
# it works!
|
||
|
|
s[timestamp]
|
||
|
|
assert len(s.loc[[timestamp]]) > 0
|
||
|
|
|
||
|
|
|
||
|
|
def test_indexing_unordered():
|
||
|
|
# GH 2437
|
||
|
|
rng = date_range(start="2011-01-01", end="2011-01-15")
|
||
|
|
ts = Series(np.random.rand(len(rng)), index=rng)
|
||
|
|
ts2 = pd.concat([ts[0:4], ts[-4:], ts[4:-4]])
|
||
|
|
|
||
|
|
for t in ts.index:
|
||
|
|
|
||
|
|
expected = ts[t]
|
||
|
|
result = ts2[t]
|
||
|
|
assert expected == result
|
||
|
|
|
||
|
|
# GH 3448 (ranges)
|
||
|
|
def compare(slobj):
|
||
|
|
result = ts2[slobj].copy()
|
||
|
|
result = result.sort_index()
|
||
|
|
expected = ts[slobj]
|
||
|
|
expected.index = expected.index._with_freq(None)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
compare(slice("2011-01-01", "2011-01-15"))
|
||
|
|
with tm.assert_produces_warning(FutureWarning):
|
||
|
|
compare(slice("2010-12-30", "2011-01-15"))
|
||
|
|
compare(slice("2011-01-01", "2011-01-16"))
|
||
|
|
|
||
|
|
# partial ranges
|
||
|
|
compare(slice("2011-01-01", "2011-01-6"))
|
||
|
|
compare(slice("2011-01-06", "2011-01-8"))
|
||
|
|
compare(slice("2011-01-06", "2011-01-12"))
|
||
|
|
|
||
|
|
# single values
|
||
|
|
result = ts2["2011"].sort_index()
|
||
|
|
expected = ts["2011"]
|
||
|
|
expected.index = expected.index._with_freq(None)
|
||
|
|
tm.assert_series_equal(result, expected)
|
||
|
|
|
||
|
|
# diff freq
|
||
|
|
rng = date_range(datetime(2005, 1, 1), periods=20, freq="M")
|
||
|
|
ts = Series(np.arange(len(rng)), index=rng)
|
||
|
|
ts = ts.take(np.random.permutation(20))
|
||
|
|
|
||
|
|
result = ts["2005"]
|
||
|
|
for t in result.index:
|
||
|
|
assert t.year == 2005
|
||
|
|
|
||
|
|
|
||
|
|
def test_indexing():
|
||
|
|
idx = date_range("2001-1-1", periods=20, freq="M")
|
||
|
|
ts = Series(np.random.rand(len(idx)), index=idx)
|
||
|
|
|
||
|
|
# getting
|
||
|
|
|
||
|
|
# GH 3070, make sure semantics work on Series/Frame
|
||
|
|
expected = ts["2001"]
|
||
|
|
expected.name = "A"
|
||
|
|
|
||
|
|
df = DataFrame({"A": ts})
|
||
|
|
with tm.assert_produces_warning(FutureWarning):
|
||
|
|
# GH#36179 string indexing on rows for DataFrame deprecated
|
||
|
|
result = df["2001"]["A"]
|
||
|
|
tm.assert_series_equal(expected, result)
|
||
|
|
|
||
|
|
# setting
|
||
|
|
ts["2001"] = 1
|
||
|
|
expected = ts["2001"]
|
||
|
|
expected.name = "A"
|
||
|
|
|
||
|
|
df.loc["2001", "A"] = 1
|
||
|
|
|
||
|
|
with tm.assert_produces_warning(FutureWarning):
|
||
|
|
# GH#36179 string indexing on rows for DataFrame deprecated
|
||
|
|
result = df["2001"]["A"]
|
||
|
|
tm.assert_series_equal(expected, result)
|
||
|
|
|
||
|
|
# GH3546 (not including times on the last day)
|
||
|
|
idx = date_range(start="2013-05-31 00:00", end="2013-05-31 23:00", freq="H")
|
||
|
|
ts = Series(range(len(idx)), index=idx)
|
||
|
|
expected = ts["2013-05"]
|
||
|
|
tm.assert_series_equal(expected, ts)
|
||
|
|
|
||
|
|
idx = date_range(start="2013-05-31 00:00", end="2013-05-31 23:59", freq="S")
|
||
|
|
ts = Series(range(len(idx)), index=idx)
|
||
|
|
expected = ts["2013-05"]
|
||
|
|
tm.assert_series_equal(expected, ts)
|
||
|
|
|
||
|
|
idx = [
|
||
|
|
Timestamp("2013-05-31 00:00"),
|
||
|
|
Timestamp(datetime(2013, 5, 31, 23, 59, 59, 999999)),
|
||
|
|
]
|
||
|
|
ts = Series(range(len(idx)), index=idx)
|
||
|
|
expected = ts["2013"]
|
||
|
|
tm.assert_series_equal(expected, ts)
|
||
|
|
|
||
|
|
# GH14826, indexing with a seconds resolution string / datetime object
|
||
|
|
df = DataFrame(
|
||
|
|
np.random.rand(5, 5),
|
||
|
|
columns=["open", "high", "low", "close", "volume"],
|
||
|
|
index=date_range("2012-01-02 18:01:00", periods=5, tz="US/Central", freq="s"),
|
||
|
|
)
|
||
|
|
expected = df.loc[[df.index[2]]]
|
||
|
|
|
||
|
|
# this is a single date, so will raise
|
||
|
|
with pytest.raises(KeyError, match=r"^'2012-01-02 18:01:02'$"):
|
||
|
|
df["2012-01-02 18:01:02"]
|
||
|
|
msg = r"Timestamp\('2012-01-02 18:01:02-0600', tz='US/Central', freq='S'\)"
|
||
|
|
with pytest.raises(KeyError, match=msg):
|
||
|
|
df[df.index[2]]
|