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Merged
merged 7 commits into from
Feb 12, 2018
Merged

move array_to_datetime timests #19640

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494fb99
move array_to_datetime timests
jbrockmendel Feb 10, 2018
7d5d21e
fixup typo, parametrize
jbrockmendel Feb 11, 2018
ec455c8
Merge branch 'master' of https://github.com/pandas-dev/pandas into it…
jbrockmendel Feb 11, 2018
fc47604
format
jbrockmendel Feb 11, 2018
195f793
remove unused import
jbrockmendel Feb 11, 2018
294273e
Merge branch 'master' into PR_TOOL_MERGE_PR_19640
jreback Feb 12, 2018
2e6ac8c
clean
jreback Feb 12, 2018
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175 changes: 9 additions & 166 deletions pandas/tests/indexes/datetimes/test_tools.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,6 @@

from pandas.errors import OutOfBoundsDatetime
from pandas.compat import lmap, PY3
from pandas.compat.numpy import np_array_datetime64_compat
from pandas.core.dtypes.common import is_datetime64_ns_dtype
from pandas.util import testing as tm
import pandas.util._test_decorators as td
Expand Down Expand Up @@ -791,6 +790,15 @@ def test_dataframe_dtypes(self, cache):


class TestToDatetimeMisc(object):
def test_to_datetime_barely_out_of_bounds(self):
# GH#19529
# GH#19382 close enough to bounds that dropping nanos would result
# in an in-bounds datetime
arr = np.array(['2262-04-11 23:47:16.854775808'], dtype=object)

with pytest.raises(OutOfBoundsDatetime):
to_datetime(arr)

@pytest.mark.parametrize('cache', [True, False])
def test_to_datetime_iso8601(self, cache):
result = to_datetime(["2012-01-01 00:00:00"], cache=cache)
Expand Down Expand Up @@ -1452,171 +1460,6 @@ def test_parsers_timezone_minute_offsets_roundtrip(self, cache):
converted_time = dt_time.tz_localize('UTC').tz_convert(tz)
assert dt_string_repr == repr(converted_time)

def test_parsers_iso8601(self):
# GH 12060
# test only the iso parser - flexibility to different
# separators and leadings 0s
# Timestamp construction falls back to dateutil
cases = {'2011-01-02': datetime(2011, 1, 2),
'2011-1-2': datetime(2011, 1, 2),
'2011-01': datetime(2011, 1, 1),
'2011-1': datetime(2011, 1, 1),
'2011 01 02': datetime(2011, 1, 2),
'2011.01.02': datetime(2011, 1, 2),
'2011/01/02': datetime(2011, 1, 2),
'2011\\01\\02': datetime(2011, 1, 2),
'2013-01-01 05:30:00': datetime(2013, 1, 1, 5, 30),
'2013-1-1 5:30:00': datetime(2013, 1, 1, 5, 30)}
for date_str, exp in compat.iteritems(cases):
actual = tslib._test_parse_iso8601(date_str)
assert actual == exp

# separators must all match - YYYYMM not valid
invalid_cases = ['2011-01/02', '2011^11^11',
'201401', '201111', '200101',
# mixed separated and unseparated
'2005-0101', '200501-01',
'20010101 12:3456', '20010101 1234:56',
# HHMMSS must have two digits in each component
# if unseparated
'20010101 1', '20010101 123', '20010101 12345',
'20010101 12345Z',
# wrong separator for HHMMSS
'2001-01-01 12-34-56']
for date_str in invalid_cases:
with pytest.raises(ValueError):
tslib._test_parse_iso8601(date_str)
# If no ValueError raised, let me know which case failed.
raise Exception(date_str)


class TestArrayToDatetime(object):
def test_parsing_valid_dates(self):
arr = np.array(['01-01-2013', '01-02-2013'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr),
np_array_datetime64_compat(
[
'2013-01-01T00:00:00.000000000-0000',
'2013-01-02T00:00:00.000000000-0000'
],
dtype='M8[ns]'
)
)

arr = np.array(['Mon Sep 16 2013', 'Tue Sep 17 2013'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr),
np_array_datetime64_compat(
[
'2013-09-16T00:00:00.000000000-0000',
'2013-09-17T00:00:00.000000000-0000'
],
dtype='M8[ns]'
)
)

def test_parsing_timezone_offsets(self):
# All of these datetime strings with offsets are equivalent
# to the same datetime after the timezone offset is added
dt_strings = [
'01-01-2013 08:00:00+08:00',
'2013-01-01T08:00:00.000000000+0800',
'2012-12-31T16:00:00.000000000-0800',
'12-31-2012 23:00:00-01:00'
]

expected_output = tslib.array_to_datetime(np.array(
['01-01-2013 00:00:00'], dtype=object))

for dt_string in dt_strings:
tm.assert_numpy_array_equal(
tslib.array_to_datetime(
np.array([dt_string], dtype=object)
),
expected_output
)

def test_number_looking_strings_not_into_datetime(self):
# #4601
# These strings don't look like datetimes so they shouldn't be
# attempted to be converted
arr = np.array(['-352.737091', '183.575577'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='ignore'), arr)

arr = np.array(['1', '2', '3', '4', '5'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='ignore'), arr)

def test_coercing_dates_outside_of_datetime64_ns_bounds(self):
invalid_dates = [
date(1000, 1, 1),
datetime(1000, 1, 1),
'1000-01-01',
'Jan 1, 1000',
np.datetime64('1000-01-01'),
]

for invalid_date in invalid_dates:
pytest.raises(ValueError,
tslib.array_to_datetime,
np.array([invalid_date], dtype='object'),
errors='raise', )
tm.assert_numpy_array_equal(
tslib.array_to_datetime(
np.array([invalid_date], dtype='object'),
errors='coerce'),
np.array([tslib.iNaT], dtype='M8[ns]')
)

arr = np.array(['1/1/1000', '1/1/2000'], dtype=object)
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='coerce'),
np_array_datetime64_compat(
[
tslib.iNaT,
'2000-01-01T00:00:00.000000000-0000'
],
dtype='M8[ns]'
)
)

def test_coerce_of_invalid_datetimes(self):
arr = np.array(['01-01-2013', 'not_a_date', '1'], dtype=object)

# Without coercing, the presence of any invalid dates prevents
# any values from being converted
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='ignore'), arr)

# With coercing, the invalid dates becomes iNaT
tm.assert_numpy_array_equal(
tslib.array_to_datetime(arr, errors='coerce'),
np_array_datetime64_compat(
[
'2013-01-01T00:00:00.000000000-0000',
tslib.iNaT,
tslib.iNaT
],
dtype='M8[ns]'
)
)

def test_to_datetime_barely_out_of_bounds(self):
# GH#19529
# GH#19382 close enough to bounds that dropping nanos would result
# in an in-bounds datetime
arr = np.array(['2262-04-11 23:47:16.854775808'], dtype=object)

with pytest.raises(OutOfBoundsDatetime):
to_datetime(arr)

with pytest.raises(OutOfBoundsDatetime):
# Essentially the same as above, but more directly calling
# the relevant function
tslib.array_to_datetime(arr)


def test_normalize_date():
value = date(2012, 9, 7)
Expand Down
145 changes: 145 additions & 0 deletions pandas/tests/tslibs/test_array_to_datetime.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,145 @@
# -*- coding: utf-8 -*-
from datetime import datetime, date

import numpy as np
import pytest

from pandas import compat
from pandas._libs import tslib
from pandas.compat.numpy import np_array_datetime64_compat
import pandas.util.testing as tm


class TestParseISO8601(object):
def test_parsers_iso8601(self):
# GH#12060
# test only the iso parser - flexibility to different
# separators and leadings 0s
# Timestamp construction falls back to dateutil
cases = {'2011-01-02': datetime(2011, 1, 2),
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can u parametrize

'2011-1-2': datetime(2011, 1, 2),
'2011-01': datetime(2011, 1, 1),
'2011-1': datetime(2011, 1, 1),
'2011 01 02': datetime(2011, 1, 2),
'2011.01.02': datetime(2011, 1, 2),
'2011/01/02': datetime(2011, 1, 2),
'2011\\01\\02': datetime(2011, 1, 2),
'2013-01-01 05:30:00': datetime(2013, 1, 1, 5, 30),
'2013-1-1 5:30:00': datetime(2013, 1, 1, 5, 30)}
for date_str, exp in compat.iteritems(cases):
actual = tslib._test_parse_iso8601(date_str)
assert actual == exp

@pytest.mark.parametrize('date_str', ['2011-01/02', '2011^11^11',
'201401', '201111', '200101',
# mixed separated and unseparated
'2005-0101', '200501-01',
'20010101 12:3456',
'20010101 1234:56',
# HHMMSS must have two digits in
# each component if unseparated
'20010101 1', '20010101 123',
'20010101 12345', '20010101 12345Z',
# wrong separator for HHMMSS
'2001-01-01 12-34-56'])
def test_parsers_iso8601_invalid(self, date_str):
# separators must all match - YYYYMM not valid
with pytest.raises(ValueError):
tslib._test_parse_iso8601(date_str)
# If no ValueError raised, let me know which case failed.
raise Exception(date_str)
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this is not necessary and the point off parametering

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can you remove this except



class TestArrayToDatetime(object):
def test_parsing_valid_dates(self):
arr = np.array(['01-01-2013', '01-02-2013'], dtype=object)
result = tslib.array_to_datetime(arr)
expected = ['2013-01-01T00:00:00.000000000-0000',
'2013-01-02T00:00:00.000000000-0000']
tm.assert_numpy_array_equal(result,
np_array_datetime64_compat(expected,
dtype='M8[ns]'))

arr = np.array(['Mon Sep 16 2013', 'Tue Sep 17 2013'], dtype=object)
result = tslib.array_to_datetime(arr)
expected = ['2013-09-16T00:00:00.000000000-0000',
'2013-09-17T00:00:00.000000000-0000']
tm.assert_numpy_array_equal(result,
np_array_datetime64_compat(expected,
dtype='M8[ns]'))

@pytest.mark.parametrize('dt_string', [
'01-01-2013 08:00:00+08:00',
'2013-01-01T08:00:00.000000000+0800',
'2012-12-31T16:00:00.000000000-0800',
'12-31-2012 23:00:00-01:00'])
def test_parsing_timezone_offsets(self, dt_string):
# All of these datetime strings with offsets are equivalent
# to the same datetime after the timezone offset is added
arr = np.array(['01-01-2013 00:00:00'], dtype=object)
expected = tslib.array_to_datetime(arr)

arr = np.array([dt_string], dtype=object)
result = tslib.array_to_datetime(arr)
tm.assert_numpy_array_equal(result, expected)

def test_number_looking_strings_not_into_datetime(self):
# GH#4601
# These strings don't look like datetimes so they shouldn't be
# attempted to be converted
arr = np.array(['-352.737091', '183.575577'], dtype=object)
result = tslib.array_to_datetime(arr, errors='ignore')
tm.assert_numpy_array_equal(result, arr)

arr = np.array(['1', '2', '3', '4', '5'], dtype=object)
result = tslib.array_to_datetime(arr, errors='ignore')
tm.assert_numpy_array_equal(result, arr)

@pytest.mark.parametrize('invalid_date', [date(1000, 1, 1),
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pls format this

datetime(1000, 1, 1),
'1000-01-01',
'Jan 1, 1000',
np.datetime64('1000-01-01')])
def test_coerce_outside_ns_bounds(self, invalid_date):
arr = np.array([invalid_date], dtype='object')
with pytest.raises(ValueError):
tslib.array_to_datetime(arr, errors='raise')

result = tslib.array_to_datetime(arr, errors='coerce')
expected = np.array([tslib.iNaT], dtype='M8[ns]')
tm.assert_numpy_array_equal(result, expected)

def test_coerce_outside_ns_bounds_one_valid(self):
arr = np.array(['1/1/1000', '1/1/2000'], dtype=object)
result = tslib.array_to_datetime(arr, errors='coerce')
expected = [tslib.iNaT,
'2000-01-01T00:00:00.000000000-0000'],
tm.assert_numpy_array_equal(result,
np_array_datetime64_compat(expected,
dtype='M8[ns]'))

def test_coerce_of_invalid_datetimes(self):
arr = np.array(['01-01-2013', 'not_a_date', '1'], dtype=object)

# Without coercing, the presence of any invalid dates prevents
# any values from being converted
result = tslib.array_to_datetime(arr, errors='ignore')
tm.assert_numpy_array_equal(result, arr)

# With coercing, the invalid dates becomes iNaT
result = tslib.array_to_datetime(arr, errors='coerce')
expected = ['2013-01-01T00:00:00.000000000-0000',
tslib.iNaT,
tslib.iNaT]

tm.assert_numpy_array_equal(result,
np_array_datetime64_compat(expected,
dtype='M8[ns]'))

def test_to_datetime_barely_out_of_bounds(self):
# GH#19529
# GH#19382 close enough to bounds that dropping nanos would result
# in an in-bounds datetime
arr = np.array(['2262-04-11 23:47:16.854775808'], dtype=object)
with pytest.raises(tslib.OutOfBoundsDatetime):
tslib.array_to_datetime(arr)