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test_tools.py
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""" test to_datetime """
import calendar
from datetime import datetime, time
from distutils.version import LooseVersion
import locale
import dateutil
from dateutil.parser import parse
from dateutil.tz.tz import tzoffset
import numpy as np
import pytest
import pytz
from pandas._libs import tslib
from pandas._libs.tslibs import iNaT, parsing
from pandas.compat import lmap
from pandas.errors import OutOfBoundsDatetime
import pandas.util._test_decorators as td
from pandas.core.dtypes.common import is_datetime64_ns_dtype
import pandas as pd
from pandas import (
DataFrame, DatetimeIndex, Index, NaT, Series, Timestamp, date_range, isna,
to_datetime)
from pandas.core.arrays import DatetimeArray
from pandas.core.tools import datetimes as tools
from pandas.util import testing as tm
from pandas.util.testing import assert_series_equal
class TestTimeConversionFormats:
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_format(self, cache):
values = ['1/1/2000', '1/2/2000', '1/3/2000']
results1 = [Timestamp('20000101'), Timestamp('20000201'),
Timestamp('20000301')]
results2 = [Timestamp('20000101'), Timestamp('20000102'),
Timestamp('20000103')]
for vals, expecteds in [(values, (Index(results1), Index(results2))),
(Series(values),
(Series(results1), Series(results2))),
(values[0], (results1[0], results2[0])),
(values[1], (results1[1], results2[1])),
(values[2], (results1[2], results2[2]))]:
for i, fmt in enumerate(['%d/%m/%Y', '%m/%d/%Y']):
result = to_datetime(vals, format=fmt, cache=cache)
expected = expecteds[i]
if isinstance(expected, Series):
assert_series_equal(result, Series(expected))
elif isinstance(expected, Timestamp):
assert result == expected
else:
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_format_YYYYMMDD(self, cache):
s = Series([19801222, 19801222] + [19810105] * 5)
expected = Series([Timestamp(x) for x in s.apply(str)])
result = to_datetime(s, format='%Y%m%d', cache=cache)
assert_series_equal(result, expected)
result = to_datetime(s.apply(str), format='%Y%m%d', cache=cache)
assert_series_equal(result, expected)
# with NaT
expected = Series([Timestamp("19801222"), Timestamp("19801222")] +
[Timestamp("19810105")] * 5)
expected[2] = np.nan
s[2] = np.nan
result = to_datetime(s, format='%Y%m%d', cache=cache)
assert_series_equal(result, expected)
# string with NaT
s = s.apply(str)
s[2] = 'nat'
result = to_datetime(s, format='%Y%m%d', cache=cache)
assert_series_equal(result, expected)
# coercion
# GH 7930
s = Series([20121231, 20141231, 99991231])
result = pd.to_datetime(s, format='%Y%m%d', errors='ignore',
cache=cache)
expected = Series([datetime(2012, 12, 31),
datetime(2014, 12, 31), datetime(9999, 12, 31)],
dtype=object)
tm.assert_series_equal(result, expected)
result = pd.to_datetime(s, format='%Y%m%d', errors='coerce',
cache=cache)
expected = Series(['20121231', '20141231', 'NaT'], dtype='M8[ns]')
assert_series_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_format_integer(self, cache):
# GH 10178
s = Series([2000, 2001, 2002])
expected = Series([Timestamp(x) for x in s.apply(str)])
result = to_datetime(s, format='%Y', cache=cache)
assert_series_equal(result, expected)
s = Series([200001, 200105, 200206])
expected = Series([Timestamp(x[:4] + '-' + x[4:]) for x in s.apply(str)
])
result = to_datetime(s, format='%Y%m', cache=cache)
assert_series_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_format_microsecond(self, cache):
# these are locale dependent
lang, _ = locale.getlocale()
month_abbr = calendar.month_abbr[4]
val = '01-{}-2011 00:00:01.978'.format(month_abbr)
format = '%d-%b-%Y %H:%M:%S.%f'
result = to_datetime(val, format=format, cache=cache)
exp = datetime.strptime(val, format)
assert result == exp
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_format_time(self, cache):
data = [
['01/10/2010 15:20', '%m/%d/%Y %H:%M',
Timestamp('2010-01-10 15:20')],
['01/10/2010 05:43', '%m/%d/%Y %I:%M',
Timestamp('2010-01-10 05:43')],
['01/10/2010 13:56:01', '%m/%d/%Y %H:%M:%S',
Timestamp('2010-01-10 13:56:01')] # ,
# ['01/10/2010 08:14 PM', '%m/%d/%Y %I:%M %p',
# Timestamp('2010-01-10 20:14')],
# ['01/10/2010 07:40 AM', '%m/%d/%Y %I:%M %p',
# Timestamp('2010-01-10 07:40')],
# ['01/10/2010 09:12:56 AM', '%m/%d/%Y %I:%M:%S %p',
# Timestamp('2010-01-10 09:12:56')]
]
for s, format, dt in data:
assert to_datetime(s, format=format, cache=cache) == dt
@td.skip_if_has_locale
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_with_non_exact(self, cache):
# GH 10834
# 8904
# exact kw
s = Series(['19MAY11', 'foobar19MAY11', '19MAY11:00:00:00',
'19MAY11 00:00:00Z'])
result = to_datetime(s, format='%d%b%y', exact=False, cache=cache)
expected = to_datetime(s.str.extract(r'(\d+\w+\d+)', expand=False),
format='%d%b%y', cache=cache)
assert_series_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_parse_nanoseconds_with_formula(self, cache):
# GH8989
# trunctaing the nanoseconds when a format was provided
for v in ["2012-01-01 09:00:00.000000001",
"2012-01-01 09:00:00.000001",
"2012-01-01 09:00:00.001",
"2012-01-01 09:00:00.001000",
"2012-01-01 09:00:00.001000000", ]:
expected = pd.to_datetime(v, cache=cache)
result = pd.to_datetime(v, format="%Y-%m-%d %H:%M:%S.%f",
cache=cache)
assert result == expected
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_format_weeks(self, cache):
data = [
['2009324', '%Y%W%w', Timestamp('2009-08-13')],
['2013020', '%Y%U%w', Timestamp('2013-01-13')]
]
for s, format, dt in data:
assert to_datetime(s, format=format, cache=cache) == dt
@pytest.mark.parametrize("fmt,dates,expected_dates", [
['%Y-%m-%d %H:%M:%S %Z',
['2010-01-01 12:00:00 UTC'] * 2,
[pd.Timestamp('2010-01-01 12:00:00', tz='UTC')] * 2],
['%Y-%m-%d %H:%M:%S %Z',
['2010-01-01 12:00:00 UTC',
'2010-01-01 12:00:00 GMT',
'2010-01-01 12:00:00 US/Pacific'],
[pd.Timestamp('2010-01-01 12:00:00', tz='UTC'),
pd.Timestamp('2010-01-01 12:00:00', tz='GMT'),
pd.Timestamp('2010-01-01 12:00:00', tz='US/Pacific')]],
['%Y-%m-%d %H:%M:%S%z',
['2010-01-01 12:00:00+0100'] * 2,
[pd.Timestamp('2010-01-01 12:00:00',
tzinfo=pytz.FixedOffset(60))] * 2],
['%Y-%m-%d %H:%M:%S %z',
['2010-01-01 12:00:00 +0100'] * 2,
[pd.Timestamp('2010-01-01 12:00:00',
tzinfo=pytz.FixedOffset(60))] * 2],
['%Y-%m-%d %H:%M:%S %z',
['2010-01-01 12:00:00 +0100', '2010-01-01 12:00:00 -0100'],
[pd.Timestamp('2010-01-01 12:00:00',
tzinfo=pytz.FixedOffset(60)),
pd.Timestamp('2010-01-01 12:00:00',
tzinfo=pytz.FixedOffset(-60))]],
['%Y-%m-%d %H:%M:%S %z',
['2010-01-01 12:00:00 Z', '2010-01-01 12:00:00 Z'],
[pd.Timestamp('2010-01-01 12:00:00',
tzinfo=pytz.FixedOffset(0)), # pytz coerces to UTC
pd.Timestamp('2010-01-01 12:00:00',
tzinfo=pytz.FixedOffset(0))]]])
def test_to_datetime_parse_tzname_or_tzoffset(self, fmt, dates,
expected_dates):
# GH 13486
result = pd.to_datetime(dates, format=fmt)
expected = pd.Index(expected_dates)
tm.assert_equal(result, expected)
with pytest.raises(ValueError):
pd.to_datetime(dates, format=fmt, utc=True)
@pytest.mark.parametrize('offset', [
'+0', '-1foo', 'UTCbar', ':10', '+01:000:01', ''])
def test_to_datetime_parse_timezone_malformed(self, offset):
fmt = '%Y-%m-%d %H:%M:%S %z'
date = '2010-01-01 12:00:00 ' + offset
with pytest.raises(ValueError):
pd.to_datetime([date], format=fmt)
def test_to_datetime_parse_timezone_keeps_name(self):
# GH 21697
fmt = '%Y-%m-%d %H:%M:%S %z'
arg = pd.Index(['2010-01-01 12:00:00 Z'], name='foo')
result = pd.to_datetime(arg, format=fmt)
expected = pd.DatetimeIndex(['2010-01-01 12:00:00'], tz='UTC',
name='foo')
tm.assert_index_equal(result, expected)
class TestToDatetime:
@pytest.mark.parametrize("s, _format, dt", [
['2015-1-1', '%G-%V-%u', datetime(2014, 12, 29, 0, 0)],
['2015-1-4', '%G-%V-%u', datetime(2015, 1, 1, 0, 0)],
['2015-1-7', '%G-%V-%u', datetime(2015, 1, 4, 0, 0)]
])
def test_to_datetime_iso_week_year_format(self, s, _format, dt):
# See GH#16607
assert to_datetime(s, format=_format) == dt
@pytest.mark.parametrize("msg, s, _format", [
["ISO week directive '%V' must be used with the ISO year directive "
"'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", "1999 50",
"%Y %V"],
["ISO year directive '%G' must be used with the ISO week directive "
"'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", "1999 51",
"%G %V"],
["ISO year directive '%G' must be used with the ISO week directive "
"'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", "1999 "
"Monday", "%G %A"],
["ISO year directive '%G' must be used with the ISO week directive "
"'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", "1999 Mon",
"%G %a"],
["ISO year directive '%G' must be used with the ISO week directive "
"'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", "1999 6",
"%G %w"],
["ISO year directive '%G' must be used with the ISO week directive "
"'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", "1999 6",
"%G %u"],
["ISO year directive '%G' must be used with the ISO week directive "
"'%V' and a weekday directive '%A', '%a', '%w', or '%u'.", "2051",
"%G"],
["Day of the year directive '%j' is not compatible with ISO year "
"directive '%G'. Use '%Y' instead.", "1999 51 6 256", "%G %V %u %j"],
["ISO week directive '%V' is incompatible with the year directive "
"'%Y'. Use the ISO year '%G' instead.", "1999 51 Sunday", "%Y %V %A"],
["ISO week directive '%V' is incompatible with the year directive "
"'%Y'. Use the ISO year '%G' instead.", "1999 51 Sun", "%Y %V %a"],
["ISO week directive '%V' is incompatible with the year directive "
"'%Y'. Use the ISO year '%G' instead.", "1999 51 1", "%Y %V %w"],
["ISO week directive '%V' is incompatible with the year directive "
"'%Y'. Use the ISO year '%G' instead.", "1999 51 1", "%Y %V %u"],
["ISO week directive '%V' must be used with the ISO year directive "
"'%G' and a weekday directive '%A', '%a', '%w', or '%u'.", "20", "%V"]
])
def test_error_iso_week_year(self, msg, s, _format):
# See GH#16607
# This test checks for errors thrown when giving the wrong format
# However, as discussed on PR#25541, overriding the locale
# causes a different error to be thrown due to the format being
# locale specific, but the test data is in english.
# Therefore, the tests only run when locale is not overwritten,
# as a sort of solution to this problem.
if (locale.getlocale() != ('zh_CN', 'UTF-8') and
locale.getlocale() != ('it_IT', 'UTF-8')):
with pytest.raises(ValueError, match=msg):
to_datetime(s, format=_format)
@pytest.mark.parametrize('tz', [None, 'US/Central'])
def test_to_datetime_dtarr(self, tz):
# DatetimeArray
dti = date_range('1965-04-03', periods=19, freq='2W', tz=tz)
arr = DatetimeArray(dti)
result = to_datetime(arr)
assert result is arr
result = to_datetime(arr)
assert result is arr
def test_to_datetime_pydatetime(self):
actual = pd.to_datetime(datetime(2008, 1, 15))
assert actual == datetime(2008, 1, 15)
def test_to_datetime_YYYYMMDD(self):
actual = pd.to_datetime('20080115')
assert actual == datetime(2008, 1, 15)
def test_to_datetime_unparseable_ignore(self):
# unparseable
s = 'Month 1, 1999'
assert pd.to_datetime(s, errors='ignore') == s
@td.skip_if_windows # `tm.set_timezone` does not work in windows
def test_to_datetime_now(self):
# See GH#18666
with tm.set_timezone('US/Eastern'):
npnow = np.datetime64('now').astype('datetime64[ns]')
pdnow = pd.to_datetime('now')
pdnow2 = pd.to_datetime(['now'])[0]
# These should all be equal with infinite perf; this gives
# a generous margin of 10 seconds
assert abs(pdnow.value - npnow.astype(np.int64)) < 1e10
assert abs(pdnow2.value - npnow.astype(np.int64)) < 1e10
assert pdnow.tzinfo is None
assert pdnow2.tzinfo is None
@td.skip_if_windows # `tm.set_timezone` does not work in windows
def test_to_datetime_today(self):
# See GH#18666
# Test with one timezone far ahead of UTC and another far behind, so
# one of these will _almost_ alawys be in a different day from UTC.
# Unfortunately this test between 12 and 1 AM Samoa time
# this both of these timezones _and_ UTC will all be in the same day,
# so this test will not detect the regression introduced in #18666.
with tm.set_timezone('Pacific/Auckland'): # 12-13 hours ahead of UTC
nptoday = np.datetime64('today')\
.astype('datetime64[ns]').astype(np.int64)
pdtoday = pd.to_datetime('today')
pdtoday2 = pd.to_datetime(['today'])[0]
tstoday = pd.Timestamp('today')
tstoday2 = pd.Timestamp.today()
# These should all be equal with infinite perf; this gives
# a generous margin of 10 seconds
assert abs(pdtoday.normalize().value - nptoday) < 1e10
assert abs(pdtoday2.normalize().value - nptoday) < 1e10
assert abs(pdtoday.value - tstoday.value) < 1e10
assert abs(pdtoday.value - tstoday2.value) < 1e10
assert pdtoday.tzinfo is None
assert pdtoday2.tzinfo is None
with tm.set_timezone('US/Samoa'): # 11 hours behind UTC
nptoday = np.datetime64('today')\
.astype('datetime64[ns]').astype(np.int64)
pdtoday = pd.to_datetime('today')
pdtoday2 = pd.to_datetime(['today'])[0]
# These should all be equal with infinite perf; this gives
# a generous margin of 10 seconds
assert abs(pdtoday.normalize().value - nptoday) < 1e10
assert abs(pdtoday2.normalize().value - nptoday) < 1e10
assert pdtoday.tzinfo is None
assert pdtoday2.tzinfo is None
def test_to_datetime_today_now_unicode_bytes(self):
to_datetime(['now'])
to_datetime(['today'])
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_dt64s(self, cache):
in_bound_dts = [
np.datetime64('2000-01-01'),
np.datetime64('2000-01-02'),
]
for dt in in_bound_dts:
assert pd.to_datetime(dt, cache=cache) == Timestamp(dt)
@pytest.mark.parametrize('dt', [np.datetime64('1000-01-01'),
np.datetime64('5000-01-02')])
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_dt64s_out_of_bounds(self, cache, dt):
msg = "Out of bounds nanosecond timestamp: {}".format(dt)
with pytest.raises(OutOfBoundsDatetime, match=msg):
pd.to_datetime(dt, errors='raise')
with pytest.raises(OutOfBoundsDatetime, match=msg):
Timestamp(dt)
assert pd.to_datetime(dt, errors='coerce', cache=cache) is NaT
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_array_of_dt64s(self, cache):
dts = [np.datetime64('2000-01-01'), np.datetime64('2000-01-02'), ]
# Assuming all datetimes are in bounds, to_datetime() returns
# an array that is equal to Timestamp() parsing
tm.assert_index_equal(
pd.to_datetime(dts, cache=cache),
pd.DatetimeIndex([Timestamp(x).asm8 for x in dts])
)
# A list of datetimes where the last one is out of bounds
dts_with_oob = dts + [np.datetime64('9999-01-01')]
msg = "Out of bounds nanosecond timestamp: 9999-01-01 00:00:00"
with pytest.raises(OutOfBoundsDatetime, match=msg):
pd.to_datetime(dts_with_oob, errors='raise')
tm.assert_index_equal(
pd.to_datetime(dts_with_oob, errors='coerce',
cache=cache),
pd.DatetimeIndex(
[
Timestamp(dts_with_oob[0]).asm8,
Timestamp(dts_with_oob[1]).asm8,
pd.NaT
]
)
)
# With errors='ignore', out of bounds datetime64s
# are converted to their .item(), which depending on the version of
# numpy is either a python datetime.datetime or datetime.date
tm.assert_index_equal(
pd.to_datetime(dts_with_oob, errors='ignore',
cache=cache),
pd.Index(
[dt.item() for dt in dts_with_oob]
)
)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_tz(self, cache):
# xref 8260
# uniform returns a DatetimeIndex
arr = [pd.Timestamp('2013-01-01 13:00:00-0800', tz='US/Pacific'),
pd.Timestamp('2013-01-02 14:00:00-0800', tz='US/Pacific')]
result = pd.to_datetime(arr, cache=cache)
expected = DatetimeIndex(
['2013-01-01 13:00:00', '2013-01-02 14:00:00'], tz='US/Pacific')
tm.assert_index_equal(result, expected)
# mixed tzs will raise
arr = [pd.Timestamp('2013-01-01 13:00:00', tz='US/Pacific'),
pd.Timestamp('2013-01-02 14:00:00', tz='US/Eastern')]
msg = ("Tz-aware datetime.datetime cannot be converted to datetime64"
" unless utc=True")
with pytest.raises(ValueError, match=msg):
pd.to_datetime(arr, cache=cache)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_tz_pytz(self, cache):
# see gh-8260
us_eastern = pytz.timezone('US/Eastern')
arr = np.array([us_eastern.localize(datetime(year=2000, month=1, day=1,
hour=3, minute=0)),
us_eastern.localize(datetime(year=2000, month=6, day=1,
hour=3, minute=0))],
dtype=object)
result = pd.to_datetime(arr, utc=True, cache=cache)
expected = DatetimeIndex(['2000-01-01 08:00:00+00:00',
'2000-06-01 07:00:00+00:00'],
dtype='datetime64[ns, UTC]', freq=None)
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
@pytest.mark.parametrize("init_constructor, end_constructor, test_method",
[(Index, DatetimeIndex, tm.assert_index_equal),
(list, DatetimeIndex, tm.assert_index_equal),
(np.array, DatetimeIndex, tm.assert_index_equal),
(Series, Series, tm.assert_series_equal)])
def test_to_datetime_utc_true(self,
cache,
init_constructor,
end_constructor,
test_method):
# See gh-11934 & gh-6415
data = ['20100102 121314', '20100102 121315']
expected_data = [pd.Timestamp('2010-01-02 12:13:14', tz='utc'),
pd.Timestamp('2010-01-02 12:13:15', tz='utc')]
result = pd.to_datetime(init_constructor(data),
format='%Y%m%d %H%M%S',
utc=True,
cache=cache)
expected = end_constructor(expected_data)
test_method(result, expected)
# Test scalar case as well
for scalar, expected in zip(data, expected_data):
result = pd.to_datetime(scalar, format='%Y%m%d %H%M%S', utc=True,
cache=cache)
assert result == expected
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_utc_true_with_series_single_value(self, cache):
# GH 15760 UTC=True with Series
ts = 1.5e18
result = pd.to_datetime(pd.Series([ts]), utc=True, cache=cache)
expected = pd.Series([pd.Timestamp(ts, tz='utc')])
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_utc_true_with_series_tzaware_string(self, cache):
ts = '2013-01-01 00:00:00-01:00'
expected_ts = '2013-01-01 01:00:00'
data = pd.Series([ts] * 3)
result = pd.to_datetime(data, utc=True, cache=cache)
expected = pd.Series([pd.Timestamp(expected_ts, tz='utc')] * 3)
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
@pytest.mark.parametrize('date, dtype',
[('2013-01-01 01:00:00', 'datetime64[ns]'),
('2013-01-01 01:00:00', 'datetime64[ns, UTC]')])
def test_to_datetime_utc_true_with_series_datetime_ns(self, cache, date,
dtype):
expected = pd.Series([pd.Timestamp('2013-01-01 01:00:00', tz='UTC')])
result = pd.to_datetime(pd.Series([date], dtype=dtype), utc=True,
cache=cache)
tm.assert_series_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_tz_psycopg2(self, cache):
# xref 8260
try:
import psycopg2
except ImportError:
pytest.skip("no psycopg2 installed")
# misc cases
tz1 = psycopg2.tz.FixedOffsetTimezone(offset=-300, name=None)
tz2 = psycopg2.tz.FixedOffsetTimezone(offset=-240, name=None)
arr = np.array([datetime(2000, 1, 1, 3, 0, tzinfo=tz1),
datetime(2000, 6, 1, 3, 0, tzinfo=tz2)],
dtype=object)
result = pd.to_datetime(arr, errors='coerce', utc=True, cache=cache)
expected = DatetimeIndex(['2000-01-01 08:00:00+00:00',
'2000-06-01 07:00:00+00:00'],
dtype='datetime64[ns, UTC]', freq=None)
tm.assert_index_equal(result, expected)
# dtype coercion
i = pd.DatetimeIndex([
'2000-01-01 08:00:00'
], tz=psycopg2.tz.FixedOffsetTimezone(offset=-300, name=None))
assert is_datetime64_ns_dtype(i)
# tz coerceion
result = pd.to_datetime(i, errors='coerce', cache=cache)
tm.assert_index_equal(result, i)
result = pd.to_datetime(i, errors='coerce', utc=True, cache=cache)
expected = pd.DatetimeIndex(['2000-01-01 13:00:00'],
dtype='datetime64[ns, UTC]')
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize(
'cache',
[pytest.param(True,
marks=pytest.mark.skipif(True, reason="GH 18111")),
False])
def test_datetime_bool(self, cache):
# GH13176
with pytest.raises(TypeError):
to_datetime(False)
assert to_datetime(False, errors="coerce", cache=cache) is NaT
assert to_datetime(False, errors="ignore", cache=cache) is False
with pytest.raises(TypeError):
to_datetime(True)
assert to_datetime(True, errors="coerce", cache=cache) is NaT
assert to_datetime(True, errors="ignore", cache=cache) is True
with pytest.raises(TypeError):
to_datetime([False, datetime.today()], cache=cache)
with pytest.raises(TypeError):
to_datetime(['20130101', True], cache=cache)
tm.assert_index_equal(to_datetime([0, False, NaT, 0.0],
errors="coerce", cache=cache),
DatetimeIndex([to_datetime(0, cache=cache),
NaT,
NaT,
to_datetime(0, cache=cache)]))
def test_datetime_invalid_datatype(self):
# GH13176
with pytest.raises(TypeError):
pd.to_datetime(bool)
with pytest.raises(TypeError):
pd.to_datetime(pd.to_datetime)
@pytest.mark.parametrize('value', ["a", "00:01:99"])
@pytest.mark.parametrize('infer', [True, False])
@pytest.mark.parametrize('format', [None, 'H%:M%:S%'])
def test_datetime_invalid_scalar(self, value, format, infer):
# GH24763
res = pd.to_datetime(value, errors='ignore', format=format,
infer_datetime_format=infer)
assert res == value
res = pd.to_datetime(value, errors='coerce', format=format,
infer_datetime_format=infer)
assert res is pd.NaT
with pytest.raises(ValueError):
pd.to_datetime(value, errors='raise', format=format,
infer_datetime_format=infer)
@pytest.mark.parametrize('value', ["3000/12/11 00:00:00"])
@pytest.mark.parametrize('infer', [True, False])
@pytest.mark.parametrize('format', [None, 'H%:M%:S%'])
def test_datetime_outofbounds_scalar(self, value, format, infer):
# GH24763
res = pd.to_datetime(value, errors='ignore', format=format,
infer_datetime_format=infer)
assert res == value
res = pd.to_datetime(value, errors='coerce', format=format,
infer_datetime_format=infer)
assert res is pd.NaT
if format is not None:
with pytest.raises(ValueError):
pd.to_datetime(value, errors='raise', format=format,
infer_datetime_format=infer)
else:
with pytest.raises(OutOfBoundsDatetime):
pd.to_datetime(value, errors='raise', format=format,
infer_datetime_format=infer)
@pytest.mark.parametrize('values', [["a"], ["00:01:99"],
["a", "b", "99:00:00"]])
@pytest.mark.parametrize('infer', [True, False])
@pytest.mark.parametrize('format', [None, 'H%:M%:S%'])
def test_datetime_invalid_index(self, values, format, infer):
# GH24763
res = pd.to_datetime(values, errors='ignore', format=format,
infer_datetime_format=infer)
tm.assert_index_equal(res, pd.Index(values))
res = pd.to_datetime(values, errors='coerce', format=format,
infer_datetime_format=infer)
tm.assert_index_equal(res, pd.DatetimeIndex([pd.NaT] * len(values)))
with pytest.raises(ValueError):
pd.to_datetime(values, errors='raise', format=format,
infer_datetime_format=infer)
@pytest.mark.parametrize("utc", [True, None])
@pytest.mark.parametrize("format", ['%Y%m%d %H:%M:%S', None])
@pytest.mark.parametrize("constructor", [list, tuple, np.array, pd.Index])
def test_to_datetime_cache(self, utc, format, constructor):
date = '20130101 00:00:00'
test_dates = [date] * 10**5
data = constructor(test_dates)
result = pd.to_datetime(data, utc=utc, format=format, cache=True)
expected = pd.to_datetime(data, utc=utc, format=format, cache=False)
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize("utc", [True, None])
@pytest.mark.parametrize("format", ['%Y%m%d %H:%M:%S', None])
def test_to_datetime_cache_series(self, utc, format):
date = '20130101 00:00:00'
test_dates = [date] * 10**5
data = pd.Series(test_dates)
result = pd.to_datetime(data, utc=utc, format=format, cache=True)
expected = pd.to_datetime(data, utc=utc, format=format, cache=False)
tm.assert_series_equal(result, expected)
def test_to_datetime_cache_scalar(self):
date = '20130101 00:00:00'
result = pd.to_datetime(date, cache=True)
expected = pd.Timestamp('20130101 00:00:00')
assert result == expected
@pytest.mark.parametrize('date, format',
[('2017-20', '%Y-%W'),
('20 Sunday', '%W %A'),
('20 Sun', '%W %a'),
('2017-21', '%Y-%U'),
('20 Sunday', '%U %A'),
('20 Sun', '%U %a')])
def test_week_without_day_and_calendar_year(self, date, format):
# GH16774
msg = "Cannot use '%W' or '%U' without day and year"
with pytest.raises(ValueError, match=msg):
pd.to_datetime(date, format=format)
def test_iso_8601_strings_with_same_offset(self):
# GH 17697, 11736
ts_str = "2015-11-18 15:30:00+05:30"
result = to_datetime(ts_str)
expected = Timestamp(ts_str)
assert result == expected
expected = DatetimeIndex([Timestamp(ts_str)] * 2)
result = to_datetime([ts_str] * 2)
tm.assert_index_equal(result, expected)
result = DatetimeIndex([ts_str] * 2)
tm.assert_index_equal(result, expected)
def test_iso_8601_strings_same_offset_no_box(self):
# GH 22446
data = ['2018-01-04 09:01:00+09:00', '2018-01-04 09:02:00+09:00']
with tm.assert_produces_warning(FutureWarning):
result = pd.to_datetime(data, box=False)
expected = np.array([
datetime(2018, 1, 4, 9, 1, tzinfo=pytz.FixedOffset(540)),
datetime(2018, 1, 4, 9, 2, tzinfo=pytz.FixedOffset(540))
],
dtype=object)
tm.assert_numpy_array_equal(result, expected)
def test_iso_8601_strings_with_different_offsets(self):
# GH 17697, 11736
ts_strings = ["2015-11-18 15:30:00+05:30",
"2015-11-18 16:30:00+06:30",
NaT]
result = to_datetime(ts_strings)
expected = np.array([datetime(2015, 11, 18, 15, 30,
tzinfo=tzoffset(None, 19800)),
datetime(2015, 11, 18, 16, 30,
tzinfo=tzoffset(None, 23400)),
NaT],
dtype=object)
# GH 21864
expected = Index(expected)
tm.assert_index_equal(result, expected)
result = to_datetime(ts_strings, utc=True)
expected = DatetimeIndex([Timestamp(2015, 11, 18, 10),
Timestamp(2015, 11, 18, 10),
NaT], tz='UTC')
tm.assert_index_equal(result, expected)
def test_iso8601_strings_mixed_offsets_with_naive(self):
# GH 24992
result = pd.to_datetime([
'2018-11-28T00:00:00',
'2018-11-28T00:00:00+12:00',
'2018-11-28T00:00:00',
'2018-11-28T00:00:00+06:00',
'2018-11-28T00:00:00'
], utc=True)
expected = pd.to_datetime([
'2018-11-28T00:00:00',
'2018-11-27T12:00:00',
'2018-11-28T00:00:00',
'2018-11-27T18:00:00',
'2018-11-28T00:00:00'
], utc=True)
tm.assert_index_equal(result, expected)
items = ['2018-11-28T00:00:00+12:00', '2018-11-28T00:00:00']
result = pd.to_datetime(items, utc=True)
expected = pd.to_datetime(list(reversed(items)), utc=True)[::-1]
tm.assert_index_equal(result, expected)
def test_mixed_offsets_with_native_datetime_raises(self):
# GH 25978
s = pd.Series([
'nan',
pd.Timestamp("1990-01-01"),
"2015-03-14T16:15:14.123-08:00",
"2019-03-04T21:56:32.620-07:00",
None,
])
with pytest.raises(ValueError, match="Tz-aware datetime.datetime"):
pd.to_datetime(s)
def test_non_iso_strings_with_tz_offset(self):
result = to_datetime(['March 1, 2018 12:00:00+0400'] * 2)
expected = DatetimeIndex([datetime(2018, 3, 1, 12,
tzinfo=pytz.FixedOffset(240))] * 2)
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize('ts, expected', [
(Timestamp('2018-01-01'),
Timestamp('2018-01-01', tz='UTC')),
(Timestamp('2018-01-01', tz='US/Pacific'),
Timestamp('2018-01-01 08:00', tz='UTC'))])
def test_timestamp_utc_true(self, ts, expected):
# GH 24415
result = to_datetime(ts, utc=True)
assert result == expected
def test_to_datetime_box_deprecated(self):
expected = np.datetime64('2018-09-09')
# Deprecated - see GH24416
with tm.assert_produces_warning(FutureWarning):
pd.to_datetime(expected, box=False)
result = pd.to_datetime(expected).to_datetime64()
assert result == expected
class TestToDatetimeUnit:
@pytest.mark.parametrize('cache', [True, False])
def test_unit(self, cache):
# GH 11758
# test proper behavior with erros
with pytest.raises(ValueError):
to_datetime([1], unit='D', format='%Y%m%d', cache=cache)
values = [11111111, 1, 1.0, iNaT, NaT, np.nan,
'NaT', '']
result = to_datetime(values, unit='D', errors='ignore', cache=cache)
expected = Index([11111111, Timestamp('1970-01-02'),
Timestamp('1970-01-02'), NaT,
NaT, NaT, NaT, NaT],
dtype=object)
tm.assert_index_equal(result, expected)
result = to_datetime(values, unit='D', errors='coerce', cache=cache)
expected = DatetimeIndex(['NaT', '1970-01-02', '1970-01-02',
'NaT', 'NaT', 'NaT', 'NaT', 'NaT'])
tm.assert_index_equal(result, expected)
with pytest.raises(tslib.OutOfBoundsDatetime):
to_datetime(values, unit='D', errors='raise', cache=cache)
values = [1420043460000, iNaT, NaT, np.nan, 'NaT']
result = to_datetime(values, errors='ignore', unit='s', cache=cache)
expected = Index([1420043460000, NaT, NaT,
NaT, NaT], dtype=object)
tm.assert_index_equal(result, expected)
result = to_datetime(values, errors='coerce', unit='s', cache=cache)
expected = DatetimeIndex(['NaT', 'NaT', 'NaT', 'NaT', 'NaT'])
tm.assert_index_equal(result, expected)
with pytest.raises(tslib.OutOfBoundsDatetime):
to_datetime(values, errors='raise', unit='s', cache=cache)
# if we have a string, then we raise a ValueError
# and NOT an OutOfBoundsDatetime
for val in ['foo', Timestamp('20130101')]:
try:
to_datetime(val, errors='raise', unit='s', cache=cache)
except tslib.OutOfBoundsDatetime:
raise AssertionError("incorrect exception raised")
except ValueError:
pass
@pytest.mark.parametrize('cache', [True, False])
def test_unit_consistency(self, cache):
# consistency of conversions
expected = Timestamp('1970-05-09 14:25:11')
result = pd.to_datetime(11111111, unit='s', errors='raise',
cache=cache)
assert result == expected
assert isinstance(result, Timestamp)
result = pd.to_datetime(11111111, unit='s', errors='coerce',
cache=cache)
assert result == expected
assert isinstance(result, Timestamp)
result = pd.to_datetime(11111111, unit='s', errors='ignore',
cache=cache)
assert result == expected
assert isinstance(result, Timestamp)
@pytest.mark.parametrize('cache', [True, False])
def test_unit_with_numeric(self, cache):
# GH 13180
# coercions from floats/ints are ok
expected = DatetimeIndex(['2015-06-19 05:33:20',
'2015-05-27 22:33:20'])
arr1 = [1.434692e+18, 1.432766e+18]
arr2 = np.array(arr1).astype('int64')
for errors in ['ignore', 'raise', 'coerce']:
result = pd.to_datetime(arr1, errors=errors, cache=cache)
tm.assert_index_equal(result, expected)
result = pd.to_datetime(arr2, errors=errors, cache=cache)
tm.assert_index_equal(result, expected)
# but we want to make sure that we are coercing
# if we have ints/strings
expected = DatetimeIndex(['NaT',
'2015-06-19 05:33:20',
'2015-05-27 22:33:20'])
arr = ['foo', 1.434692e+18, 1.432766e+18]
result = pd.to_datetime(arr, errors='coerce', cache=cache)
tm.assert_index_equal(result, expected)
expected = DatetimeIndex(['2015-06-19 05:33:20',
'2015-05-27 22:33:20',
'NaT',
'NaT'])
arr = [1.434692e+18, 1.432766e+18, 'foo', 'NaT']
result = pd.to_datetime(arr, errors='coerce', cache=cache)
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_unit_mixed(self, cache):
# mixed integers/datetimes
expected = DatetimeIndex(['2013-01-01', 'NaT', 'NaT'])
arr = [pd.Timestamp('20130101'), 1.434692e+18, 1.432766e+18]
result = pd.to_datetime(arr, errors='coerce', cache=cache)
tm.assert_index_equal(result, expected)
with pytest.raises(ValueError):
pd.to_datetime(arr, errors='raise', cache=cache)
expected = DatetimeIndex(['NaT',
'NaT',
'2013-01-01'])
arr = [1.434692e+18, 1.432766e+18, pd.Timestamp('20130101')]
result = pd.to_datetime(arr, errors='coerce', cache=cache)
tm.assert_index_equal(result, expected)
with pytest.raises(ValueError):
pd.to_datetime(arr, errors='raise', cache=cache)
@pytest.mark.parametrize('cache', [True, False])
def test_unit_rounding(self, cache):
# GH 14156: argument will incur floating point errors but no
# premature rounding
result = pd.to_datetime(1434743731.8770001, unit='s', cache=cache)
expected = pd.Timestamp('2015-06-19 19:55:31.877000093')
assert result == expected
@pytest.mark.parametrize('cache', [True, False])
def test_unit_ignore_keeps_name(self, cache):
# GH 21697
expected = pd.Index([15e9] * 2, name='name')
result = pd.to_datetime(expected, errors='ignore', unit='s',
cache=cache)
tm.assert_index_equal(result, expected)
@pytest.mark.parametrize('cache', [True, False])
def test_dataframe(self, cache):
df = DataFrame({'year': [2015, 2016],
'month': [2, 3],
'day': [4, 5],
'hour': [6, 7],
'minute': [58, 59],
'second': [10, 11],
'ms': [1, 1],
'us': [2, 2],
'ns': [3, 3]})
result = to_datetime({'year': df['year'],
'month': df['month'],
'day': df['day']}, cache=cache)
expected = Series([Timestamp('20150204 00:00:00'),
Timestamp('20160305 00:0:00')])
assert_series_equal(result, expected)
# dict-like
result = to_datetime(df[['year', 'month', 'day']].to_dict(),
cache=cache)
assert_series_equal(result, expected)
# dict but with constructable
df2 = df[['year', 'month', 'day']].to_dict()
df2['month'] = 2
result = to_datetime(df2, cache=cache)
expected2 = Series([Timestamp('20150204 00:00:00'),
Timestamp('20160205 00:0:00')])
assert_series_equal(result, expected2)