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TST: move pandas/tests/io/test_date_converters.py to pandas/tests/io/parsers/parse_dates.py #15707

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TST: move pandas/tests/io/test_date_converters.py to pandas/tests/io/parsers/parse_dates.py #15707

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b977615
Merge remote-tracking branch 'pandas-dev/master'
jaehoonhwang Mar 8, 2017
9b20caa
Merge remote-tracking branch 'pandas-dev/master'
jaehoonhwang Mar 16, 2017
3eb63c5
TST15519 Moving Unit tests to appropriate file
jaehoonhwang Mar 16, 2017
e019e95
Imported read_table and using self.readcsv
jaehoonhwang Mar 17, 2017
ef6e8fa
Fixing up few lines and imports
jaehoonhwang Mar 17, 2017
0b309d3
Fixed frame email and PEP8
jaehoonhwang Mar 18, 2017
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147 changes: 147 additions & 0 deletions pandas/tests/io/parser/parse_dates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,8 @@
from pandas import DataFrame, Series, Index, DatetimeIndex
from pandas import compat
from pandas.compat import parse_date, StringIO, lrange
from pandas.compat.numpy import np_array_datetime64_compat
from pandas.io.parsers import read_table
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don't use read_table

instead these should use self.read_csv

from pandas.tseries.index import date_range


Expand Down Expand Up @@ -510,3 +512,148 @@ def test_parse_date_time_multi_level_column_name(self):
expected = DataFrame(expected_data,
columns=['date_time', ('A', 'a'), ('B', 'b')])
tm.assert_frame_equal(result, expected)

def test_parse_date_time(self):
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things that are strictly related the the actual parsing (e.g. just involve conv) can be put in a separate class; name it TestConverters (otherwise it won't be run)

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actually nvm about this comment

# From test_date_coverter
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this comment not needed

dates = np.array(['2007/1/3', '2008/2/4'], dtype=object)
times = np.array(['05:07:09', '06:08:00'], dtype=object)
expected = np.array([datetime(2007, 1, 3, 5, 7, 9),
datetime(2008, 2, 4, 6, 8, 0)])

result = conv.parse_date_time(dates, times)
self.assertTrue((result == expected).all())

data = """\
date, time, a, b
2001-01-05, 10:00:00, 0.0, 10.
2001-01-05, 00:00:00, 1., 11.
"""
datecols = {'date_time': [0, 1]}
df = read_table(StringIO(data), sep=',', header=0,
parse_dates=datecols, date_parser=conv.parse_date_time)
self.assertIn('date_time', df)
self.assertEqual(df.date_time.loc[0], datetime(2001, 1, 5, 10, 0, 0))

data = ("KORD,19990127, 19:00:00, 18:56:00, 0.8100\n"
"KORD,19990127, 20:00:00, 19:56:00, 0.0100\n"
"KORD,19990127, 21:00:00, 20:56:00, -0.5900\n"
"KORD,19990127, 21:00:00, 21:18:00, -0.9900\n"
"KORD,19990127, 22:00:00, 21:56:00, -0.5900\n"
"KORD,19990127, 23:00:00, 22:56:00, -0.5900")

date_spec = {'nominal': [1, 2], 'actual': [1, 3]}
df = read_csv(StringIO(data), header=None, parse_dates=date_spec,
date_parser=conv.parse_date_time)

def test_parse_date_fields(self):
years = np.array([2007, 2008])
months = np.array([1, 2])
days = np.array([3, 4])
result = conv.parse_date_fields(years, months, days)
expected = np.array([datetime(2007, 1, 3), datetime(2008, 2, 4)])
self.assertTrue((result == expected).all())

data = ("year, month, day, a\n 2001 , 01 , 10 , 10.\n"
"2001 , 02 , 1 , 11.")
datecols = {'ymd': [0, 1, 2]}
df = read_table(StringIO(data), sep=',', header=0,
parse_dates=datecols,
date_parser=conv.parse_date_fields)
self.assertIn('ymd', df)
self.assertEqual(df.ymd.loc[0], datetime(2001, 1, 10))

def test_datetime_six_col(self):
years = np.array([2007, 2008])
months = np.array([1, 2])
days = np.array([3, 4])
hours = np.array([5, 6])
minutes = np.array([7, 8])
seconds = np.array([9, 0])
expected = np.array([datetime(2007, 1, 3, 5, 7, 9),
datetime(2008, 2, 4, 6, 8, 0)])

result = conv.parse_all_fields(years, months, days,
hours, minutes, seconds)


self.assertTrue((result == expected).all())

data = """\
year, month, day, hour, minute, second, a, b
2001, 01, 05, 10, 00, 0, 0.0, 10.
2001, 01, 5, 10, 0, 00, 1., 11.
"""
datecols = {'ymdHMS': [0, 1, 2, 3, 4, 5]}
df = read_table(StringIO(data), sep=',', header=0,
parse_dates=datecols,
date_parser=conv.parse_all_fields)
self.assertIn('ymdHMS', df)
self.assertEqual(df.ymdHMS.loc[0], datetime(2001, 1, 5, 10, 0, 0))

def test_datetime_fractional_seconds(self):
data = """\
year, month, day, hour, minute, second, a, b
2001, 01, 05, 10, 00, 0.123456, 0.0, 10.
2001, 01, 5, 10, 0, 0.500000, 1., 11.
"""
datecols = {'ymdHMS': [0, 1, 2, 3, 4, 5]}
df = read_table(StringIO(data), sep=',', header=0,
parse_dates=datecols,
date_parser=conv.parse_all_fields)
self.assertIn('ymdHMS', df)
self.assertEqual(df.ymdHMS.loc[0], datetime(2001, 1, 5, 10, 0, 0,
microsecond=123456))
self.assertEqual(df.ymdHMS.loc[1], datetime(2001, 1, 5, 10, 0, 0,
microsecond=500000))

def test_generic(self):
data = "year, month, day, a\n 2001, 01, 10, 10.\n 2001, 02, 1, 11."
datecols = {'ym': [0, 1]}
dateconverter = lambda y, m: date(year=int(y), month=int(m), day=1)
df = read_table(StringIO(data), sep=',', header=0,
parse_dates=datecols,
date_parser=dateconverter)
self.assertIn('ym', df)
self.assertEqual(df.ym.loc[0], date(2001, 1, 1))

def test_dateparser_resolution_if_not_ns(self):
# GH 10245
data = """\
date,time,prn,rxstatus
2013-11-03,19:00:00,126,00E80000
2013-11-03,19:00:00,23,00E80000
2013-11-03,19:00:00,13,00E80000
"""

def date_parser(date, time):
datetime = np_array_datetime64_compat(
date + 'T' + time + 'Z', dtype='datetime64[s]')
return datetime


df = self.read_csv(StringIO(data), date_parser=date_parser,
parse_dates={'datetime': ['date', 'time']},
index_col=['datetime', 'prn'])

datetimes = np_array_datetime64_compat(['2013-11-03T19:00:00Z'] * 3,
dtype='datetime64[s]')
df_correct = DataFrame(data={'rxstatus': ['00E80000'] * 3},
index=MultiIndex.from_tuples(
[(datetimes[0], 126),
(datetimes[1], 23),
(datetimes[2], 13)],
names=['datetime', 'prn']))
assert_frame_equal(df, df_correct)

def test_parse_date_column_with_empty_string(self):
# GH 6428
data = """case,opdate
7,10/18/2006
7,10/18/2008
621, """
result = self.read_csv(StringIO(data), parse_dates=['opdate'])
expected_data = [[7, '10/18/2006'],
[7, '10/18/2008'],
[621, ' ']]
expected = DataFrame(expected_data, columns=['case', 'opdate'])
assert_frame_equal(result, expected)