import numpy as np import pytest from pandas import DataFrame, Series, date_range, period_range import pandas._testing as tm class TestPeriodIndex: def test_pindex_slice_index(self): pi = period_range(start="1/1/10", end="12/31/12", freq="M") s = Series(np.random.rand(len(pi)), index=pi) res = s["2010"] exp = s[0:12] tm.assert_series_equal(res, exp) res = s["2011"] exp = s[12:24] tm.assert_series_equal(res, exp) @pytest.mark.parametrize("make_range", [date_range, period_range]) def test_range_slice_day(self, make_range): # GH#6716 idx = make_range(start="2013/01/01", freq="D", periods=400) msg = "slice indices must be integers or None or have an __index__ method" # slices against index should raise IndexError values = [ "2014", "2013/02", "2013/01/02", "2013/02/01 9H", "2013/02/01 09:00", ] for v in values: with pytest.raises(TypeError, match=msg): idx[v:] s = Series(np.random.rand(len(idx)), index=idx) tm.assert_series_equal(s["2013/01/02":], s[1:]) tm.assert_series_equal(s["2013/01/02":"2013/01/05"], s[1:5]) tm.assert_series_equal(s["2013/02":], s[31:]) tm.assert_series_equal(s["2014":], s[365:]) invalid = ["2013/02/01 9H", "2013/02/01 09:00"] for v in invalid: with pytest.raises(TypeError, match=msg): idx[v:] @pytest.mark.parametrize("make_range", [date_range, period_range]) def test_range_slice_seconds(self, make_range): # GH#6716 idx = make_range(start="2013/01/01 09:00:00", freq="S", periods=4000) msg = "slice indices must be integers or None or have an __index__ method" # slices against index should raise IndexError values = [ "2014", "2013/02", "2013/01/02", "2013/02/01 9H", "2013/02/01 09:00", ] for v in values: with pytest.raises(TypeError, match=msg): idx[v:] s = Series(np.random.rand(len(idx)), index=idx) tm.assert_series_equal(s["2013/01/01 09:05":"2013/01/01 09:10"], s[300:660]) tm.assert_series_equal(s["2013/01/01 10:00":"2013/01/01 10:05"], s[3600:3960]) tm.assert_series_equal(s["2013/01/01 10H":], s[3600:]) tm.assert_series_equal(s[:"2013/01/01 09:30"], s[:1860]) for d in ["2013/01/01", "2013/01", "2013"]: tm.assert_series_equal(s[d:], s) @pytest.mark.parametrize("make_range", [date_range, period_range]) def test_range_slice_outofbounds(self, make_range): # GH#5407 idx = make_range(start="2013/10/01", freq="D", periods=10) df = DataFrame({"units": [100 + i for i in range(10)]}, index=idx) empty = DataFrame(index=type(idx)([], freq="D"), columns=["units"]) empty["units"] = empty["units"].astype("int64") tm.assert_frame_equal(df["2013/09/01":"2013/09/30"], empty) tm.assert_frame_equal(df["2013/09/30":"2013/10/02"], df.iloc[:2]) tm.assert_frame_equal(df["2013/10/01":"2013/10/02"], df.iloc[:2]) tm.assert_frame_equal(df["2013/10/02":"2013/09/30"], empty) tm.assert_frame_equal(df["2013/10/15":"2013/10/17"], empty) tm.assert_frame_equal(df["2013-06":"2013-09"], empty) tm.assert_frame_equal(df["2013-11":"2013-12"], empty) @pytest.mark.parametrize("make_range", [date_range, period_range]) def test_maybe_cast_slice_bound(self, make_range, frame_or_series): idx = make_range(start="2013/10/01", freq="D", periods=10) obj = DataFrame({"units": [100 + i for i in range(10)]}, index=idx) if frame_or_series is not DataFrame: obj = obj["units"] msg = ( f"cannot do slice indexing on {type(idx).__name__} with " r"these indexers \[foo\] of type str" ) # Check the lower-level calls are raising where expected. with pytest.raises(TypeError, match=msg): idx._maybe_cast_slice_bound("foo", "left", "loc") with pytest.raises(TypeError, match=msg): idx.get_slice_bound("foo", "left", "loc") with pytest.raises(TypeError, match=msg): obj["2013/09/30":"foo"] with pytest.raises(TypeError, match=msg): obj["foo":"2013/09/30"] with pytest.raises(TypeError, match=msg): obj.loc["2013/09/30":"foo"] with pytest.raises(TypeError, match=msg): obj.loc["foo":"2013/09/30"] def test_partial_slice_doesnt_require_monotonicity(self): # See also: DatetimeIndex test ofm the same name dti = date_range("2014-01-01", periods=30, freq="30D") pi = dti.to_period("D") ser_montonic = Series(np.arange(30), index=pi) shuffler = list(range(0, 30, 2)) + list(range(1, 31, 2)) ser = ser_montonic[shuffler] nidx = ser.index # Manually identified locations of year==2014 indexer_2014 = np.array( [0, 1, 2, 3, 4, 5, 6, 15, 16, 17, 18, 19, 20], dtype=np.intp ) assert (nidx[indexer_2014].year == 2014).all() assert not (nidx[~indexer_2014].year == 2014).any() result = nidx.get_loc("2014") tm.assert_numpy_array_equal(result, indexer_2014) expected = ser[indexer_2014] with tm.assert_produces_warning(FutureWarning): result = nidx.get_value(ser, "2014") tm.assert_series_equal(result, expected) result = ser.loc["2014"] tm.assert_series_equal(result, expected) result = ser["2014"] tm.assert_series_equal(result, expected) # Manually identified locations where ser.index is within Mat 2015 indexer_may2015 = np.array([23], dtype=np.intp) assert nidx[23].year == 2015 and nidx[23].month == 5 result = nidx.get_loc("May 2015") tm.assert_numpy_array_equal(result, indexer_may2015) expected = ser[indexer_may2015] with tm.assert_produces_warning(FutureWarning): result = nidx.get_value(ser, "May 2015") tm.assert_series_equal(result, expected) result = ser.loc["May 2015"] tm.assert_series_equal(result, expected) result = ser["May 2015"] tm.assert_series_equal(result, expected)