import numpy as np import pytest import pandas as pd from pandas import DataFrame, Index, Series, Timestamp, date_range import pandas._testing as tm class TestDatetimeIndex: def test_indexing_with_datetime_tz(self): # GH#8260 # support datetime64 with tz idx = Index(date_range("20130101", periods=3, tz="US/Eastern"), name="foo") dr = date_range("20130110", periods=3) df = DataFrame({"A": idx, "B": dr}) df["C"] = idx df.iloc[1, 1] = pd.NaT df.iloc[1, 2] = pd.NaT # indexing result = df.iloc[1] expected = Series( [Timestamp("2013-01-02 00:00:00-0500", tz="US/Eastern"), pd.NaT, pd.NaT], index=list("ABC"), dtype="object", name=1, ) tm.assert_series_equal(result, expected) result = df.loc[1] expected = Series( [Timestamp("2013-01-02 00:00:00-0500", tz="US/Eastern"), pd.NaT, pd.NaT], index=list("ABC"), dtype="object", name=1, ) tm.assert_series_equal(result, expected) # indexing - fast_xs df = DataFrame({"a": date_range("2014-01-01", periods=10, tz="UTC")}) result = df.iloc[5] expected = Series( [Timestamp("2014-01-06 00:00:00+0000", tz="UTC")], index=["a"], name=5 ) tm.assert_series_equal(result, expected) result = df.loc[5] tm.assert_series_equal(result, expected) # indexing - boolean result = df[df.a > df.a[3]] expected = df.iloc[4:] tm.assert_frame_equal(result, expected) # indexing - setting an element df = DataFrame( data=pd.to_datetime(["2015-03-30 20:12:32", "2015-03-12 00:11:11"]), columns=["time"], ) df["new_col"] = ["new", "old"] df.time = df.set_index("time").index.tz_localize("UTC") v = df[df.new_col == "new"].set_index("time").index.tz_convert("US/Pacific") # trying to set a single element on a part of a different timezone # this converts to object df2 = df.copy() df2.loc[df2.new_col == "new", "time"] = v expected = Series([v[0], df.loc[1, "time"]], name="time") tm.assert_series_equal(df2.time, expected) v = df.loc[df.new_col == "new", "time"] + pd.Timedelta("1s") df.loc[df.new_col == "new", "time"] = v tm.assert_series_equal(df.loc[df.new_col == "new", "time"], v) def test_consistency_with_tz_aware_scalar(self): # xef gh-12938 # various ways of indexing the same tz-aware scalar df = Series([Timestamp("2016-03-30 14:35:25", tz="Europe/Brussels")]).to_frame() df = pd.concat([df, df]).reset_index(drop=True) expected = Timestamp("2016-03-30 14:35:25+0200", tz="Europe/Brussels") result = df[0][0] assert result == expected result = df.iloc[0, 0] assert result == expected result = df.loc[0, 0] assert result == expected result = df.iat[0, 0] assert result == expected result = df.at[0, 0] assert result == expected result = df[0].loc[0] assert result == expected result = df[0].at[0] assert result == expected def test_indexing_with_datetimeindex_tz(self): # GH 12050 # indexing on a series with a datetimeindex with tz index = date_range("2015-01-01", periods=2, tz="utc") ser = Series(range(2), index=index, dtype="int64") # list-like indexing for sel in (index, list(index)): # getitem result = ser[sel] expected = ser.copy() if sel is not index: expected.index = expected.index._with_freq(None) tm.assert_series_equal(result, expected) # setitem result = ser.copy() result[sel] = 1 expected = Series(1, index=index) tm.assert_series_equal(result, expected) # .loc getitem result = ser.loc[sel] expected = ser.copy() if sel is not index: expected.index = expected.index._with_freq(None) tm.assert_series_equal(result, expected) # .loc setitem result = ser.copy() result.loc[sel] = 1 expected = Series(1, index=index) tm.assert_series_equal(result, expected) # single element indexing # getitem assert ser[index[1]] == 1 # setitem result = ser.copy() result[index[1]] = 5 expected = Series([0, 5], index=index) tm.assert_series_equal(result, expected) # .loc getitem assert ser.loc[index[1]] == 1 # .loc setitem result = ser.copy() result.loc[index[1]] = 5 expected = Series([0, 5], index=index) tm.assert_series_equal(result, expected) @pytest.mark.parametrize("to_period", [True, False]) def test_loc_getitem_listlike_of_datetimelike_keys(self, to_period): # GH 11497 idx = date_range("2011-01-01", "2011-01-02", freq="D", name="idx") if to_period: idx = idx.to_period("D") ser = Series([0.1, 0.2], index=idx, name="s") keys = [Timestamp("2011-01-01"), Timestamp("2011-01-02")] if to_period: keys = [x.to_period("D") for x in keys] result = ser.loc[keys] exp = Series([0.1, 0.2], index=idx, name="s") if not to_period: exp.index = exp.index._with_freq(None) tm.assert_series_equal(result, exp, check_index_type=True) keys = [ Timestamp("2011-01-02"), Timestamp("2011-01-02"), Timestamp("2011-01-01"), ] if to_period: keys = [x.to_period("D") for x in keys] exp = Series( [0.2, 0.2, 0.1], index=Index(keys, name="idx", dtype=idx.dtype), name="s" ) result = ser.loc[keys] tm.assert_series_equal(result, exp, check_index_type=True) keys = [ Timestamp("2011-01-03"), Timestamp("2011-01-02"), Timestamp("2011-01-03"), ] if to_period: keys = [x.to_period("D") for x in keys] with pytest.raises(KeyError, match="with any missing labels"): ser.loc[keys] def test_nanosecond_getitem_setitem_with_tz(self): # GH 11679 data = ["2016-06-28 08:30:00.123456789"] index = pd.DatetimeIndex(data, dtype="datetime64[ns, America/Chicago]") df = DataFrame({"a": [10]}, index=index) result = df.loc[df.index[0]] expected = Series(10, index=["a"], name=df.index[0]) tm.assert_series_equal(result, expected) result = df.copy() result.loc[df.index[0], "a"] = -1 expected = DataFrame(-1, index=index, columns=["a"]) tm.assert_frame_equal(result, expected) def test_loc_setitem_with_existing_dst(self): # GH 18308 start = Timestamp("2017-10-29 00:00:00+0200", tz="Europe/Madrid") end = Timestamp("2017-10-29 03:00:00+0100", tz="Europe/Madrid") ts = Timestamp("2016-10-10 03:00:00", tz="Europe/Madrid") idx = pd.date_range(start, end, closed="left", freq="H") result = DataFrame(index=idx, columns=["value"]) result.loc[ts, "value"] = 12 expected = DataFrame( [np.nan] * len(idx) + [12], index=idx.append(pd.DatetimeIndex([ts])), columns=["value"], dtype=object, ) tm.assert_frame_equal(result, expected)