Python pandas.compat.parse_date() Examples
The following are 17
code examples of pandas.compat.parse_date().
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Example #1
| Source File: test_parse_dates.py From recruit with Apache License 2.0 | 6 votes |
|
def test_parse_dates_custom_euro_format(all_parsers, kwargs):
parser = all_parsers
data = """foo,bar,baz
31/01/2010,1,2
01/02/2010,1,NA
02/02/2010,1,2
"""
if "dayfirst" in kwargs:
df = parser.read_csv(StringIO(data), names=["time", "Q", "NTU"],
date_parser=lambda d: parse_date(d, **kwargs),
header=0, index_col=0, parse_dates=True,
na_values=["NA"])
exp_index = Index([datetime(2010, 1, 31), datetime(2010, 2, 1),
datetime(2010, 2, 2)], name="time")
expected = DataFrame({"Q": [1, 1, 1], "NTU": [2, np.nan, 2]},
index=exp_index, columns=["Q", "NTU"])
tm.assert_frame_equal(df, expected)
else:
msg = "got an unexpected keyword argument 'day_first'"
with pytest.raises(TypeError, match=msg):
parser.read_csv(StringIO(data), names=["time", "Q", "NTU"],
date_parser=lambda d: parse_date(d, **kwargs),
skiprows=[0], index_col=0, parse_dates=True,
na_values=["NA"])
Example #2
| Source File: parse_dates.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_parse_dates_custom_euroformat(self):
text = """foo,bar,baz
31/01/2010,1,2
01/02/2010,1,NA
02/02/2010,1,2
"""
parser = lambda d: parse_date(d, dayfirst=True)
df = self.read_csv(StringIO(text),
names=['time', 'Q', 'NTU'], header=0,
index_col=0, parse_dates=True,
date_parser=parser, na_values=['NA'])
exp_index = Index([datetime(2010, 1, 31), datetime(2010, 2, 1),
datetime(2010, 2, 2)], name='time')
expected = DataFrame({'Q': [1, 1, 1], 'NTU': [2, np.nan, 2]},
index=exp_index, columns=['Q', 'NTU'])
tm.assert_frame_equal(df, expected)
parser = lambda d: parse_date(d, day_first=True)
pytest.raises(TypeError, self.read_csv,
StringIO(text), skiprows=[0],
names=['time', 'Q', 'NTU'], index_col=0,
parse_dates=True, date_parser=parser,
na_values=['NA'])
Example #3
| Source File: converters.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_converters(self):
data = """A,B,C,D
a,1,2,01/01/2009
b,3,4,01/02/2009
c,4,5,01/03/2009
"""
result = self.read_csv(StringIO(data), converters={'D': parse_date})
result2 = self.read_csv(StringIO(data), converters={3: parse_date})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(parse_date)
assert isinstance(result['D'][0], (datetime, Timestamp))
tm.assert_frame_equal(result, expected)
tm.assert_frame_equal(result2, expected)
# produce integer
converter = lambda x: int(x.split('/')[2])
result = self.read_csv(StringIO(data), converters={'D': converter})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(converter)
tm.assert_frame_equal(result, expected)
Example #4
| Source File: parse_dates.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_parse_dates_custom_euroformat(self):
text = """foo,bar,baz
31/01/2010,1,2
01/02/2010,1,NA
02/02/2010,1,2
"""
parser = lambda d: parse_date(d, dayfirst=True)
df = self.read_csv(StringIO(text),
names=['time', 'Q', 'NTU'], header=0,
index_col=0, parse_dates=True,
date_parser=parser, na_values=['NA'])
exp_index = Index([datetime(2010, 1, 31), datetime(2010, 2, 1),
datetime(2010, 2, 2)], name='time')
expected = DataFrame({'Q': [1, 1, 1], 'NTU': [2, np.nan, 2]},
index=exp_index, columns=['Q', 'NTU'])
tm.assert_frame_equal(df, expected)
parser = lambda d: parse_date(d, day_first=True)
pytest.raises(TypeError, self.read_csv,
StringIO(text), skiprows=[0],
names=['time', 'Q', 'NTU'], index_col=0,
parse_dates=True, date_parser=parser,
na_values=['NA'])
Example #5
| Source File: converters.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_converters(self):
data = """A,B,C,D
a,1,2,01/01/2009
b,3,4,01/02/2009
c,4,5,01/03/2009
"""
result = self.read_csv(StringIO(data), converters={'D': parse_date})
result2 = self.read_csv(StringIO(data), converters={3: parse_date})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(parse_date)
assert isinstance(result['D'][0], (datetime, Timestamp))
tm.assert_frame_equal(result, expected)
tm.assert_frame_equal(result2, expected)
# produce integer
converter = lambda x: int(x.split('/')[2])
result = self.read_csv(StringIO(data), converters={'D': converter})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(converter)
tm.assert_frame_equal(result, expected)
Example #6
| Source File: test_parse_dates.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_parse_dates_custom_euro_format(all_parsers, kwargs):
parser = all_parsers
data = """foo,bar,baz
31/01/2010,1,2
01/02/2010,1,NA
02/02/2010,1,2
"""
if "dayfirst" in kwargs:
df = parser.read_csv(StringIO(data), names=["time", "Q", "NTU"],
date_parser=lambda d: parse_date(d, **kwargs),
header=0, index_col=0, parse_dates=True,
na_values=["NA"])
exp_index = Index([datetime(2010, 1, 31), datetime(2010, 2, 1),
datetime(2010, 2, 2)], name="time")
expected = DataFrame({"Q": [1, 1, 1], "NTU": [2, np.nan, 2]},
index=exp_index, columns=["Q", "NTU"])
tm.assert_frame_equal(df, expected)
else:
msg = "got an unexpected keyword argument 'day_first'"
with pytest.raises(TypeError, match=msg):
parser.read_csv(StringIO(data), names=["time", "Q", "NTU"],
date_parser=lambda d: parse_date(d, **kwargs),
skiprows=[0], index_col=0, parse_dates=True,
na_values=["NA"])
Example #7
| Source File: test_parsers.py From Computable with MIT License | 6 votes |
|
def test_parse_dates_custom_euroformat(self):
text = """foo,bar,baz
31/01/2010,1,2
01/02/2010,1,NA
02/02/2010,1,2
"""
parser = lambda d: parse_date(d, dayfirst=True)
df = self.read_csv(StringIO(text),
names=['time', 'Q', 'NTU'], header=0,
index_col=0, parse_dates=True,
date_parser=parser, na_values=['NA'])
exp_index = Index([datetime(2010, 1, 31), datetime(2010, 2, 1),
datetime(2010, 2, 2)], name='time')
expected = DataFrame({'Q': [1, 1, 1], 'NTU': [2, np.nan, 2]},
index=exp_index, columns=['Q', 'NTU'])
tm.assert_frame_equal(df, expected)
parser = lambda d: parse_date(d, day_first=True)
self.assertRaises(Exception, self.read_csv,
StringIO(text), skiprows=[0],
names=['time', 'Q', 'NTU'], index_col=0,
parse_dates=True, date_parser=parser,
na_values=['NA'])
Example #8
| Source File: test_parsers.py From Computable with MIT License | 6 votes |
|
def test_converters(self):
data = """A,B,C,D
a,1,2,01/01/2009
b,3,4,01/02/2009
c,4,5,01/03/2009
"""
from pandas.compat import parse_date
result = self.read_csv(StringIO(data), converters={'D': parse_date})
result2 = self.read_csv(StringIO(data), converters={3: parse_date})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(parse_date)
tm.assert_isinstance(result['D'][0], (datetime, Timestamp))
tm.assert_frame_equal(result, expected)
tm.assert_frame_equal(result2, expected)
# produce integer
converter = lambda x: int(x.split('/')[2])
result = self.read_csv(StringIO(data), converters={'D': converter})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(converter)
tm.assert_frame_equal(result, expected)
Example #9
| Source File: parse_dates.py From vnpy_crypto with MIT License | 6 votes |
|
def test_parse_dates_custom_euroformat(self):
text = """foo,bar,baz
31/01/2010,1,2
01/02/2010,1,NA
02/02/2010,1,2
"""
parser = lambda d: parse_date(d, dayfirst=True)
df = self.read_csv(StringIO(text),
names=['time', 'Q', 'NTU'], header=0,
index_col=0, parse_dates=True,
date_parser=parser, na_values=['NA'])
exp_index = Index([datetime(2010, 1, 31), datetime(2010, 2, 1),
datetime(2010, 2, 2)], name='time')
expected = DataFrame({'Q': [1, 1, 1], 'NTU': [2, np.nan, 2]},
index=exp_index, columns=['Q', 'NTU'])
tm.assert_frame_equal(df, expected)
parser = lambda d: parse_date(d, day_first=True)
pytest.raises(TypeError, self.read_csv,
StringIO(text), skiprows=[0],
names=['time', 'Q', 'NTU'], index_col=0,
parse_dates=True, date_parser=parser,
na_values=['NA'])
Example #10
| Source File: converters.py From vnpy_crypto with MIT License | 6 votes |
|
def test_converters(self):
data = """A,B,C,D
a,1,2,01/01/2009
b,3,4,01/02/2009
c,4,5,01/03/2009
"""
result = self.read_csv(StringIO(data), converters={'D': parse_date})
result2 = self.read_csv(StringIO(data), converters={3: parse_date})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(parse_date)
assert isinstance(result['D'][0], (datetime, Timestamp))
tm.assert_frame_equal(result, expected)
tm.assert_frame_equal(result2, expected)
# produce integer
converter = lambda x: int(x.split('/')[2])
result = self.read_csv(StringIO(data), converters={'D': converter})
expected = self.read_csv(StringIO(data))
expected['D'] = expected['D'].map(converter)
tm.assert_frame_equal(result, expected)
Example #11
| Source File: test_tools.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
def test_string_na_nat_conversion(self, cache):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if isna(val):
expected[i] = iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)[0]
tm.assert_almost_equal(result, expected)
result2 = to_datetime(strings, cache=cache)
assert isinstance(result2, DatetimeIndex)
tm.assert_numpy_array_equal(result, result2.values)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
# GH 10636, default is now 'raise'
pytest.raises(ValueError,
lambda: to_datetime(malformed, errors='raise',
cache=cache))
result = to_datetime(malformed, errors='ignore', cache=cache)
# GH 21864
expected = Index(malformed)
tm.assert_index_equal(result, expected)
pytest.raises(ValueError, to_datetime, malformed, errors='raise',
cache=cache)
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000', cache=cache), np.nan,
to_datetime('1/3/2000', cache=cache), np.nan,
to_datetime('1/5/2000', cache=cache)],
index=idx, name='foo')
result = to_datetime(series, cache=cache)
dresult = to_datetime(dseries, cache=cache)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isna(x):
expected[i] = iNaT
else:
expected[i] = to_datetime(x, cache=cache)
assert_series_equal(result, expected, check_names=False)
assert result.name == 'foo'
assert_series_equal(dresult, expected, check_names=False)
assert dresult.name == 'foo'
Example #12
| Source File: test_timeseries.py From Computable with MIT License | 4 votes |
|
def test_string_na_nat_conversion(self):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if com.isnull(val):
expected[i] = iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)
assert_almost_equal(result, expected)
result2 = to_datetime(strings)
tm.assert_isinstance(result2, DatetimeIndex)
assert_almost_equal(result, result2)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
result = to_datetime(malformed)
assert_almost_equal(result, malformed)
self.assertRaises(ValueError, to_datetime, malformed,
errors='raise')
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000'), np.nan,
to_datetime('1/3/2000'), np.nan,
to_datetime('1/5/2000')], index=idx, name='foo')
result = to_datetime(series)
dresult = to_datetime(dseries)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isnull(x):
expected[i] = iNaT
else:
expected[i] = to_datetime(x)
assert_series_equal(result, expected)
self.assertEquals(result.name, 'foo')
assert_series_equal(dresult, expected)
self.assertEquals(dresult.name, 'foo')
Example #13
| Source File: test_tools.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def test_string_na_nat_conversion(self):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if isna(val):
expected[i] = tslib.iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)
tm.assert_almost_equal(result, expected)
result2 = to_datetime(strings)
assert isinstance(result2, DatetimeIndex)
tm.assert_numpy_array_equal(result, result2.values)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
# GH 10636, default is now 'raise'
pytest.raises(ValueError,
lambda: to_datetime(malformed, errors='raise'))
result = to_datetime(malformed, errors='ignore')
tm.assert_numpy_array_equal(result, malformed)
pytest.raises(ValueError, to_datetime, malformed, errors='raise')
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000'), np.nan,
to_datetime('1/3/2000'), np.nan,
to_datetime('1/5/2000')], index=idx, name='foo')
result = to_datetime(series)
dresult = to_datetime(dseries)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isna(x):
expected[i] = tslib.iNaT
else:
expected[i] = to_datetime(x)
assert_series_equal(result, expected, check_names=False)
assert result.name == 'foo'
assert_series_equal(dresult, expected, check_names=False)
assert dresult.name == 'foo'
Example #14
| Source File: test_tools.py From coffeegrindsize with MIT License | 4 votes |
|
def test_string_na_nat_conversion(self, cache):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if isna(val):
expected[i] = iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)[0]
tm.assert_almost_equal(result, expected)
result2 = to_datetime(strings, cache=cache)
assert isinstance(result2, DatetimeIndex)
tm.assert_numpy_array_equal(result, result2.values)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
# GH 10636, default is now 'raise'
pytest.raises(ValueError,
lambda: to_datetime(malformed, errors='raise',
cache=cache))
result = to_datetime(malformed, errors='ignore', cache=cache)
# GH 21864
expected = Index(malformed)
tm.assert_index_equal(result, expected)
pytest.raises(ValueError, to_datetime, malformed, errors='raise',
cache=cache)
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000', cache=cache), np.nan,
to_datetime('1/3/2000', cache=cache), np.nan,
to_datetime('1/5/2000', cache=cache)],
index=idx, name='foo')
result = to_datetime(series, cache=cache)
dresult = to_datetime(dseries, cache=cache)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isna(x):
expected[i] = iNaT
else:
expected[i] = to_datetime(x, cache=cache)
assert_series_equal(result, expected, check_names=False)
assert result.name == 'foo'
assert_series_equal(dresult, expected, check_names=False)
assert dresult.name == 'foo'
Example #15
| Source File: test_tools.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def test_string_na_nat_conversion(self, cache):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if isna(val):
expected[i] = tslib.iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)
tm.assert_almost_equal(result, expected)
result2 = to_datetime(strings, cache=cache)
assert isinstance(result2, DatetimeIndex)
tm.assert_numpy_array_equal(result, result2.values)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
# GH 10636, default is now 'raise'
pytest.raises(ValueError,
lambda: to_datetime(malformed, errors='raise',
cache=cache))
result = to_datetime(malformed, errors='ignore', cache=cache)
tm.assert_numpy_array_equal(result, malformed)
pytest.raises(ValueError, to_datetime, malformed, errors='raise',
cache=cache)
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000', cache=cache), np.nan,
to_datetime('1/3/2000', cache=cache), np.nan,
to_datetime('1/5/2000', cache=cache)],
index=idx, name='foo')
result = to_datetime(series, cache=cache)
dresult = to_datetime(dseries, cache=cache)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isna(x):
expected[i] = tslib.iNaT
else:
expected[i] = to_datetime(x, cache=cache)
assert_series_equal(result, expected, check_names=False)
assert result.name == 'foo'
assert_series_equal(dresult, expected, check_names=False)
assert dresult.name == 'foo'
Example #16
| Source File: test_tools.py From vnpy_crypto with MIT License | 4 votes |
|
def test_string_na_nat_conversion(self, cache):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if isna(val):
expected[i] = tslib.iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)
tm.assert_almost_equal(result, expected)
result2 = to_datetime(strings, cache=cache)
assert isinstance(result2, DatetimeIndex)
tm.assert_numpy_array_equal(result, result2.values)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
# GH 10636, default is now 'raise'
pytest.raises(ValueError,
lambda: to_datetime(malformed, errors='raise',
cache=cache))
result = to_datetime(malformed, errors='ignore', cache=cache)
tm.assert_numpy_array_equal(result, malformed)
pytest.raises(ValueError, to_datetime, malformed, errors='raise',
cache=cache)
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000', cache=cache), np.nan,
to_datetime('1/3/2000', cache=cache), np.nan,
to_datetime('1/5/2000', cache=cache)],
index=idx, name='foo')
result = to_datetime(series, cache=cache)
dresult = to_datetime(dseries, cache=cache)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isna(x):
expected[i] = tslib.iNaT
else:
expected[i] = to_datetime(x, cache=cache)
assert_series_equal(result, expected, check_names=False)
assert result.name == 'foo'
assert_series_equal(dresult, expected, check_names=False)
assert dresult.name == 'foo'
Example #17
| Source File: test_tools.py From recruit with Apache License 2.0 | 4 votes |
|
def test_string_na_nat_conversion(self, cache):
# GH #999, #858
from pandas.compat import parse_date
strings = np.array(['1/1/2000', '1/2/2000', np.nan,
'1/4/2000, 12:34:56'], dtype=object)
expected = np.empty(4, dtype='M8[ns]')
for i, val in enumerate(strings):
if isna(val):
expected[i] = iNaT
else:
expected[i] = parse_date(val)
result = tslib.array_to_datetime(strings)[0]
tm.assert_almost_equal(result, expected)
result2 = to_datetime(strings, cache=cache)
assert isinstance(result2, DatetimeIndex)
tm.assert_numpy_array_equal(result, result2.values)
malformed = np.array(['1/100/2000', np.nan], dtype=object)
# GH 10636, default is now 'raise'
pytest.raises(ValueError,
lambda: to_datetime(malformed, errors='raise',
cache=cache))
result = to_datetime(malformed, errors='ignore', cache=cache)
# GH 21864
expected = Index(malformed)
tm.assert_index_equal(result, expected)
pytest.raises(ValueError, to_datetime, malformed, errors='raise',
cache=cache)
idx = ['a', 'b', 'c', 'd', 'e']
series = Series(['1/1/2000', np.nan, '1/3/2000', np.nan,
'1/5/2000'], index=idx, name='foo')
dseries = Series([to_datetime('1/1/2000', cache=cache), np.nan,
to_datetime('1/3/2000', cache=cache), np.nan,
to_datetime('1/5/2000', cache=cache)],
index=idx, name='foo')
result = to_datetime(series, cache=cache)
dresult = to_datetime(dseries, cache=cache)
expected = Series(np.empty(5, dtype='M8[ns]'), index=idx)
for i in range(5):
x = series[i]
if isna(x):
expected[i] = iNaT
else:
expected[i] = to_datetime(x, cache=cache)
assert_series_equal(result, expected, check_names=False)
assert result.name == 'foo'
assert_series_equal(dresult, expected, check_names=False)
assert dresult.name == 'foo'
