from datetime import datetime import dateutil.tz import numpy as np import pytest import pytz import pandas as pd from pandas import DatetimeIndex, Series import pandas._testing as tm def test_to_native_types_method_deprecated(): index = pd.date_range(freq="1D", periods=3, start="2017-01-01") expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object) with tm.assert_produces_warning(FutureWarning): result = index.to_native_types() tm.assert_numpy_array_equal(result, expected) # Make sure slicing works expected = np.array(["2017-01-01", "2017-01-03"], dtype=object) with tm.assert_produces_warning(FutureWarning): result = index.to_native_types([0, 2]) tm.assert_numpy_array_equal(result, expected) def test_to_native_types(): index = pd.date_range(freq="1D", periods=3, start="2017-01-01") # First, with no arguments. expected = np.array(["2017-01-01", "2017-01-02", "2017-01-03"], dtype=object) 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=object) result = index._format_native_types(date_format="%m-%Y-%d") tm.assert_numpy_array_equal(result, expected) # NULL object handling should work index = DatetimeIndex(["2017-01-01", pd.NaT, "2017-01-03"]) 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 TestDatetimeIndexRendering: def test_dti_repr_short(self): dr = pd.date_range(start="1/1/2012", periods=1) repr(dr) dr = pd.date_range(start="1/1/2012", periods=2) repr(dr) dr = pd.date_range(start="1/1/2012", periods=3) repr(dr) @pytest.mark.parametrize("method", ["__repr__", "__str__"]) def test_dti_representation(self, method): idxs = [] idxs.append(DatetimeIndex([], freq="D")) idxs.append(DatetimeIndex(["2011-01-01"], freq="D")) idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D")) idxs.append(DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D")) idxs.append( DatetimeIndex( ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"], freq="H", tz="Asia/Tokyo", ) ) idxs.append( DatetimeIndex( ["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="US/Eastern" ) ) idxs.append( DatetimeIndex(["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="UTC") ) exp = [] exp.append("DatetimeIndex([], dtype='datetime64[ns]', freq='D')") exp.append("DatetimeIndex(['2011-01-01'], dtype='datetime64[ns]', freq='D')") exp.append( "DatetimeIndex(['2011-01-01', '2011-01-02'], " "dtype='datetime64[ns]', freq='D')" ) exp.append( "DatetimeIndex(['2011-01-01', '2011-01-02', '2011-01-03'], " "dtype='datetime64[ns]', freq='D')" ) exp.append( "DatetimeIndex(['2011-01-01 09:00:00+09:00', " "'2011-01-01 10:00:00+09:00', '2011-01-01 11:00:00+09:00']" ", dtype='datetime64[ns, Asia/Tokyo]', freq='H')" ) exp.append( "DatetimeIndex(['2011-01-01 09:00:00-05:00', " "'2011-01-01 10:00:00-05:00', 'NaT'], " "dtype='datetime64[ns, US/Eastern]', freq=None)" ) exp.append( "DatetimeIndex(['2011-01-01 09:00:00+00:00', " "'2011-01-01 10:00:00+00:00', 'NaT'], " "dtype='datetime64[ns, UTC]', freq=None)" "" ) with pd.option_context("display.width", 300): for indx, expected in zip(idxs, exp): result = getattr(indx, method)() assert result == expected def test_dti_representation_to_series(self): idx1 = DatetimeIndex([], freq="D") idx2 = DatetimeIndex(["2011-01-01"], freq="D") idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D") idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D") idx5 = DatetimeIndex( ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"], freq="H", tz="Asia/Tokyo", ) idx6 = DatetimeIndex( ["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="US/Eastern" ) idx7 = DatetimeIndex(["2011-01-01 09:00", "2011-01-02 10:15"]) exp1 = """Series([], dtype: datetime64[ns])""" exp2 = "0 2011-01-01\ndtype: datetime64[ns]" exp3 = "0 2011-01-01\n1 2011-01-02\ndtype: datetime64[ns]" exp4 = ( "0 2011-01-01\n" "1 2011-01-02\n" "2 2011-01-03\n" "dtype: datetime64[ns]" ) exp5 = ( "0 2011-01-01 09:00:00+09:00\n" "1 2011-01-01 10:00:00+09:00\n" "2 2011-01-01 11:00:00+09:00\n" "dtype: datetime64[ns, Asia/Tokyo]" ) exp6 = ( "0 2011-01-01 09:00:00-05:00\n" "1 2011-01-01 10:00:00-05:00\n" "2 NaT\n" "dtype: datetime64[ns, US/Eastern]" ) exp7 = ( "0 2011-01-01 09:00:00\n" "1 2011-01-02 10:15:00\n" "dtype: datetime64[ns]" ) with pd.option_context("display.width", 300): for idx, expected in zip( [idx1, idx2, idx3, idx4, idx5, idx6, idx7], [exp1, exp2, exp3, exp4, exp5, exp6, exp7], ): result = repr(Series(idx)) assert result == expected def test_dti_summary(self): # GH#9116 idx1 = DatetimeIndex([], freq="D") idx2 = DatetimeIndex(["2011-01-01"], freq="D") idx3 = DatetimeIndex(["2011-01-01", "2011-01-02"], freq="D") idx4 = DatetimeIndex(["2011-01-01", "2011-01-02", "2011-01-03"], freq="D") idx5 = DatetimeIndex( ["2011-01-01 09:00", "2011-01-01 10:00", "2011-01-01 11:00"], freq="H", tz="Asia/Tokyo", ) idx6 = DatetimeIndex( ["2011-01-01 09:00", "2011-01-01 10:00", pd.NaT], tz="US/Eastern" ) exp1 = "DatetimeIndex: 0 entries\nFreq: D" exp2 = "DatetimeIndex: 1 entries, 2011-01-01 to 2011-01-01\nFreq: D" exp3 = "DatetimeIndex: 2 entries, 2011-01-01 to 2011-01-02\nFreq: D" exp4 = "DatetimeIndex: 3 entries, 2011-01-01 to 2011-01-03\nFreq: D" exp5 = ( "DatetimeIndex: 3 entries, 2011-01-01 09:00:00+09:00 " "to 2011-01-01 11:00:00+09:00\n" "Freq: H" ) exp6 = """DatetimeIndex: 3 entries, 2011-01-01 09:00:00-05:00 to NaT""" for idx, expected in zip( [idx1, idx2, idx3, idx4, idx5, idx6], [exp1, exp2, exp3, exp4, exp5, exp6] ): result = idx._summary() assert result == expected def test_dti_business_repr(self): # only really care that it works repr(pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1))) def test_dti_business_summary(self): rng = pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1)) rng._summary() rng[2:2]._summary() def test_dti_business_summary_pytz(self): pd.bdate_range("1/1/2005", "1/1/2009", tz=pytz.utc)._summary() def test_dti_business_summary_dateutil(self): pd.bdate_range("1/1/2005", "1/1/2009", tz=dateutil.tz.tzutc())._summary() def test_dti_custom_business_repr(self): # only really care that it works repr(pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1), freq="C")) def test_dti_custom_business_summary(self): rng = pd.bdate_range(datetime(2009, 1, 1), datetime(2010, 1, 1), freq="C") rng._summary() rng[2:2]._summary() def test_dti_custom_business_summary_pytz(self): pd.bdate_range("1/1/2005", "1/1/2009", freq="C", tz=pytz.utc)._summary() def test_dti_custom_business_summary_dateutil(self): pd.bdate_range( "1/1/2005", "1/1/2009", freq="C", tz=dateutil.tz.tzutc() )._summary()