import numpy as np import pytest import pandas as pd from pandas import ( PeriodIndex, Series, ) import pandas._testing as tm def test_to_native_types(): index = PeriodIndex(["2017-01-01", "2017-01-02", "2017-01-03"], freq="D") # First, with no arguments. expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype="=U10") result = index._format_native_types() tm.assert_numpy_array_equal(result, expected) # No NaN values, so na_rep has no effect result = index._format_native_types(na_rep="pandas") tm.assert_numpy_array_equal(result, expected) # Make sure date formatting works expected = np.array(["01-2017-01", "01-2017-02", "01-2017-03"], dtype="=U10") result = index._format_native_types(date_format="%m-%Y-%d") tm.assert_numpy_array_equal(result, expected) # NULL object handling should work index = PeriodIndex(["2017-01-01", pd.NaT, "2017-01-03"], freq="D") expected = np.array(["2017-01-01", "NaT", "2017-01-03"], dtype=object) result = index._format_native_types() tm.assert_numpy_array_equal(result, expected) expected = np.array(["2017-01-01", "pandas", "2017-01-03"], dtype=object) result = index._format_native_types(na_rep="pandas") tm.assert_numpy_array_equal(result, expected) class TestPeriodIndexRendering: def test_frame_repr(self): df = pd.DataFrame({"A": [1, 2, 3]}, index=pd.date_range("2000", periods=3)) result = repr(df) expected = " A\n2000-01-01 1\n2000-01-02 2\n2000-01-03 3" assert result == expected @pytest.mark.parametrize("method", ["__repr__", "__str__"]) def test_representation(self, method): # GH#7601 idx1 = PeriodIndex([], freq="D") idx2 = PeriodIndex(["2011-01-01"], freq="D") idx3 = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D") idx4 = PeriodIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D") idx5 = PeriodIndex(["2011", "2012", "2013"], freq="A") idx6 = PeriodIndex(["2011-01-01 09:00", "2012-02-01 10:00", "NaT"], freq="H") idx7 = pd.period_range("2013Q1", periods=1, freq="Q") idx8 = pd.period_range("2013Q1", periods=2, freq="Q") idx9 = pd.period_range("2013Q1", periods=3, freq="Q") idx10 = PeriodIndex(["2011-01-01", "2011-02-01"], freq="3D") exp1 = "PeriodIndex([], dtype='period[D]')" exp2 = "PeriodIndex(['2011-01-01'], dtype='period[D]')" exp3 = "PeriodIndex(['2011-01-01', '2011-01-02'], dtype='period[D]')" exp4 = ( "PeriodIndex(['2011-01-01', '2011-01-02', '2011-01-03'], " "dtype='period[D]')" ) exp5 = "PeriodIndex(['2011', '2012', '2013'], dtype='period[A-DEC]')" exp6 = ( "PeriodIndex(['2011-01-01 09:00', '2012-02-01 10:00', 'NaT'], " "dtype='period[H]')" ) exp7 = "PeriodIndex(['2013Q1'], dtype='period[Q-DEC]')" exp8 = "PeriodIndex(['2013Q1', '2013Q2'], dtype='period[Q-DEC]')" exp9 = "PeriodIndex(['2013Q1', '2013Q2', '2013Q3'], dtype='period[Q-DEC]')" exp10 = "PeriodIndex(['2011-01-01', '2011-02-01'], dtype='period[3D]')" for idx, expected in zip( [idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9, idx10], [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9, exp10], ): result = getattr(idx, method)() assert result == expected def test_representation_to_series(self): # GH#10971 idx1 = PeriodIndex([], freq="D") idx2 = PeriodIndex(["2011-01-01"], freq="D") idx3 = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D") idx4 = PeriodIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D") idx5 = PeriodIndex(["2011", "2012", "2013"], freq="A") idx6 = PeriodIndex(["2011-01-01 09:00", "2012-02-01 10:00", "NaT"], freq="H") idx7 = pd.period_range("2013Q1", periods=1, freq="Q") idx8 = pd.period_range("2013Q1", periods=2, freq="Q") idx9 = pd.period_range("2013Q1", periods=3, freq="Q") exp1 = """Series([], dtype: period[D])""" exp2 = """0 2011-01-01 dtype: period[D]""" exp3 = """0 2011-01-01 1 2011-01-02 dtype: period[D]""" exp4 = """0 2011-01-01 1 2011-01-02 2 2011-01-03 dtype: period[D]""" exp5 = """0 2011 1 2012 2 2013 dtype: period[A-DEC]""" exp6 = """0 2011-01-01 09:00 1 2012-02-01 10:00 2 NaT dtype: period[H]""" exp7 = """0 2013Q1 dtype: period[Q-DEC]""" exp8 = """0 2013Q1 1 2013Q2 dtype: period[Q-DEC]""" exp9 = """0 2013Q1 1 2013Q2 2 2013Q3 dtype: period[Q-DEC]""" for idx, expected in zip( [idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9], [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9], ): result = repr(Series(idx)) assert result == expected def test_summary(self): # GH#9116 idx1 = PeriodIndex([], freq="D") idx2 = PeriodIndex(["2011-01-01"], freq="D") idx3 = PeriodIndex(["2011-01-01", "2011-01-02"], freq="D") idx4 = PeriodIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D") idx5 = PeriodIndex(["2011", "2012", "2013"], freq="A") idx6 = PeriodIndex(["2011-01-01 09:00", "2012-02-01 10:00", "NaT"], freq="H") idx7 = pd.period_range("2013Q1", periods=1, freq="Q") idx8 = pd.period_range("2013Q1", periods=2, freq="Q") idx9 = pd.period_range("2013Q1", periods=3, freq="Q") exp1 = """PeriodIndex: 0 entries Freq: D""" exp2 = """PeriodIndex: 1 entries, 2011-01-01 to 2011-01-01 Freq: D""" exp3 = """PeriodIndex: 2 entries, 2011-01-01 to 2011-01-02 Freq: D""" exp4 = """PeriodIndex: 3 entries, 2011-01-01 to 2011-01-03 Freq: D""" exp5 = """PeriodIndex: 3 entries, 2011 to 2013 Freq: A-DEC""" exp6 = """PeriodIndex: 3 entries, 2011-01-01 09:00 to NaT Freq: H""" exp7 = """PeriodIndex: 1 entries, 2013Q1 to 2013Q1 Freq: Q-DEC""" exp8 = """PeriodIndex: 2 entries, 2013Q1 to 2013Q2 Freq: Q-DEC""" exp9 = """PeriodIndex: 3 entries, 2013Q1 to 2013Q3 Freq: Q-DEC""" for idx, expected in zip( [idx1, idx2, idx3, idx4, idx5, idx6, idx7, idx8, idx9], [exp1, exp2, exp3, exp4, exp5, exp6, exp7, exp8, exp9], ): result = idx._summary() assert result == expected