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test_formats.py
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from datetime import datetime
from pandas import DatetimeIndex, Series
import numpy as np
import dateutil.tz
import pytz
import pandas.util.testing as tm
import pandas as pd
def test_to_native_types():
index = DatetimeIndex(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.to_native_types()
tm.assert_numpy_array_equal(result, expected)
# No NaN values, so na_rep has no effect
result = index.to_native_types(na_rep='pandas')
tm.assert_numpy_array_equal(result, expected)
# Make sure slicing works
expected = np.array(['2017-01-01', '2017-01-03'], dtype=object)
result = index.to_native_types([0, 2])
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.to_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.to_native_types()
tm.assert_numpy_array_equal(result, expected)
expected = np.array(['2017-01-01', 'pandas',
'2017-01-03'], dtype=object)
result = index.to_native_types(na_rep='pandas')
tm.assert_numpy_array_equal(result, expected)
class TestDatetimeIndexRendering(object):
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)
def test_dti_representation(self):
idx = []
idx.append(DatetimeIndex([], freq='D'))
idx.append(DatetimeIndex(['2011-01-01'], freq='D'))
idx.append(DatetimeIndex(['2011-01-01', '2011-01-02'], freq='D'))
idx.append(DatetimeIndex(
['2011-01-01', '2011-01-02', '2011-01-03'], freq='D'))
idx.append(DatetimeIndex(
['2011-01-01 09:00', '2011-01-01 10:00', '2011-01-01 11:00'
], freq='H', tz='Asia/Tokyo'))
idx.append(DatetimeIndex(
['2011-01-01 09:00', '2011-01-01 10:00', pd.NaT], tz='US/Eastern'))
idx.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(idx, exp):
for func in ['__repr__', '__unicode__', '__str__']:
result = getattr(indx, func)()
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\n"
"dtype: datetime64[ns]")
exp3 = ("0 2011-01-01\n"
"1 2011-01-02\n"
"dtype: 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\n"
"Freq: D")
exp2 = ("DatetimeIndex: 1 entries, 2011-01-01 to 2011-01-01\n"
"Freq: D")
exp3 = ("DatetimeIndex: 2 entries, 2011-01-01 to 2011-01-02\n"
"Freq: D")
exp4 = ("DatetimeIndex: 3 entries, 2011-01-01 to 2011-01-03\n"
"Freq: 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()