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