Python pandas.core.strings.StringMethods() Examples
The following are 17
code examples of pandas.core.strings.StringMethods().
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Example #1
| Source File: test_strings.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_api_for_categorical(self, any_string_method):
# https://github.com/pandas-dev/pandas/issues/10661
s = Series(list('aabb'))
s = s + " " + s
c = s.astype('category')
assert isinstance(c.str, strings.StringMethods)
method_name, args, kwargs = any_string_method
result = getattr(c.str, method_name)(*args, **kwargs)
expected = getattr(s.str, method_name)(*args, **kwargs)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
elif isinstance(result, Series):
tm.assert_series_equal(result, expected)
else:
# str.cat(others=None) returns string, for example
assert result == expected
Example #2
| Source File: test_strings.py From recruit with Apache License 2.0 | 6 votes |
|
def test_api_for_categorical(self, any_string_method):
# https://github.com/pandas-dev/pandas/issues/10661
s = Series(list('aabb'))
s = s + " " + s
c = s.astype('category')
assert isinstance(c.str, strings.StringMethods)
method_name, args, kwargs = any_string_method
result = getattr(c.str, method_name)(*args, **kwargs)
expected = getattr(s.str, method_name)(*args, **kwargs)
if isinstance(result, DataFrame):
tm.assert_frame_equal(result, expected)
elif isinstance(result, Series):
tm.assert_series_equal(result, expected)
else:
# str.cat(others=None) returns string, for example
assert result == expected
Example #3
| Source File: test_strings.py From recruit with Apache License 2.0 | 5 votes |
|
def any_allowed_skipna_inferred_dtype(request):
"""
Fixture for all (inferred) dtypes allowed in StringMethods.__init__
The covered (inferred) types are:
* 'string'
* 'unicode' (if PY2)
* 'empty'
* 'bytes' (if PY3)
* 'mixed'
* 'mixed-integer'
Returns
-------
inferred_dtype : str
The string for the inferred dtype from _libs.lib.infer_dtype
values : np.ndarray
An array of object dtype that will be inferred to have
`inferred_dtype`
Examples
--------
>>> import pandas._libs.lib as lib
>>>
>>> def test_something(any_allowed_skipna_inferred_dtype):
... inferred_dtype, values = any_allowed_skipna_inferred_dtype
... # will pass
... assert lib.infer_dtype(values, skipna=True) == inferred_dtype
"""
inferred_dtype, values = request.param
values = np.array(values, dtype=object) # object dtype to avoid casting
# correctness of inference tested in tests/dtypes/test_inference.py
return inferred_dtype, values
Example #4
| Source File: test_strings.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_api(self):
# GH 6106, GH 9322
assert Series.str is strings.StringMethods
assert isinstance(Series(['']).str, strings.StringMethods)
# GH 9184
invalid = Series([1])
with tm.assert_raises_regex(AttributeError,
"only use .str accessor"):
invalid.str
assert not hasattr(invalid, 'str')
Example #5
| Source File: test_strings.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_api(self):
# GH 6106, GH 9322
assert Series.str is strings.StringMethods
assert isinstance(Series(['']).str, strings.StringMethods)
# GH 9184
invalid = Series([1])
with tm.assert_raises_regex(AttributeError,
"only use .str accessor"):
invalid.str
assert not hasattr(invalid, 'str')
Example #6
| Source File: test_strings.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_api_per_dtype(self, box, dtype, any_skipna_inferred_dtype):
# one instance of parametrized fixture
inferred_dtype, values = any_skipna_inferred_dtype
t = box(values, dtype=dtype) # explicit dtype to avoid casting
# TODO: get rid of these xfails
if dtype == 'category' and inferred_dtype in ['period', 'interval']:
pytest.xfail(reason='Conversion to numpy array fails because '
'the ._values-attribute is not a numpy array for '
'PeriodArray/IntervalArray; see GH 23553')
if box == Index and inferred_dtype in ['empty', 'bytes']:
pytest.xfail(reason='Raising too restrictively; '
'solved by GH 23167')
if (box == Index and dtype == object
and inferred_dtype in ['boolean', 'date', 'time']):
pytest.xfail(reason='Inferring incorrectly because of NaNs; '
'solved by GH 23167')
if (box == Series
and (dtype == object and inferred_dtype not in [
'string', 'unicode', 'empty',
'bytes', 'mixed', 'mixed-integer'])
or (dtype == 'category'
and inferred_dtype in ['decimal', 'boolean', 'time'])):
pytest.xfail(reason='Not raising correctly; solved by GH 23167')
types_passing_constructor = ['string', 'unicode', 'empty',
'bytes', 'mixed', 'mixed-integer']
if inferred_dtype in types_passing_constructor:
# GH 6106
assert isinstance(t.str, strings.StringMethods)
else:
# GH 9184, GH 23011, GH 23163
with pytest.raises(AttributeError, match='Can only use .str '
'accessor with string values.*'):
t.str
assert not hasattr(t, 'str')
Example #7
| Source File: test_strings.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_api(self):
# GH 6106, GH 9322
assert Series.str is strings.StringMethods
assert isinstance(Series(['']).str, strings.StringMethods)
Example #8
| Source File: test_strings.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def any_allowed_skipna_inferred_dtype(request):
"""
Fixture for all (inferred) dtypes allowed in StringMethods.__init__
The covered (inferred) types are:
* 'string'
* 'unicode' (if PY2)
* 'empty'
* 'bytes' (if PY3)
* 'mixed'
* 'mixed-integer'
Returns
-------
inferred_dtype : str
The string for the inferred dtype from _libs.lib.infer_dtype
values : np.ndarray
An array of object dtype that will be inferred to have
`inferred_dtype`
Examples
--------
>>> import pandas._libs.lib as lib
>>>
>>> def test_something(any_allowed_skipna_inferred_dtype):
... inferred_dtype, values = any_allowed_skipna_inferred_dtype
... # will pass
... assert lib.infer_dtype(values, skipna=True) == inferred_dtype
"""
inferred_dtype, values = request.param
values = np.array(values, dtype=object) # object dtype to avoid casting
# correctness of inference tested in tests/dtypes/test_inference.py
return inferred_dtype, values
Example #9
| Source File: test_strings.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def any_string_method(request):
"""
Fixture for all public methods of `StringMethods`
This fixture returns a tuple of the method name and sample arguments
necessary to call the method.
Returns
-------
method_name : str
The name of the method in `StringMethods`
args : tuple
Sample values for the positional arguments
kwargs : dict
Sample values for the keyword arguments
Examples
--------
>>> def test_something(any_string_method):
... s = pd.Series(['a', 'b', np.nan, 'd'])
...
... method_name, args, kwargs = any_string_method
... method = getattr(s.str, method_name)
... # will not raise
... method(*args, **kwargs)
"""
return request.param
# subset of the full set from pandas/conftest.py
Example #10
| Source File: series.py From Computable with MIT License | 5 votes |
|
def str(self):
from pandas.core.strings import StringMethods
return StringMethods(self)
Example #11
| Source File: test_strings.py From vnpy_crypto with MIT License | 5 votes |
|
def test_api(self):
# GH 6106, GH 9322
assert Series.str is strings.StringMethods
assert isinstance(Series(['']).str, strings.StringMethods)
# GH 9184
invalid = Series([1])
with tm.assert_raises_regex(AttributeError,
"only use .str accessor"):
invalid.str
assert not hasattr(invalid, 'str')
Example #12
| Source File: test_strings.py From recruit with Apache License 2.0 | 5 votes |
|
def test_api_per_dtype(self, box, dtype, any_skipna_inferred_dtype):
# one instance of parametrized fixture
inferred_dtype, values = any_skipna_inferred_dtype
t = box(values, dtype=dtype) # explicit dtype to avoid casting
# TODO: get rid of these xfails
if dtype == 'category' and inferred_dtype in ['period', 'interval']:
pytest.xfail(reason='Conversion to numpy array fails because '
'the ._values-attribute is not a numpy array for '
'PeriodArray/IntervalArray; see GH 23553')
if box == Index and inferred_dtype in ['empty', 'bytes']:
pytest.xfail(reason='Raising too restrictively; '
'solved by GH 23167')
if (box == Index and dtype == object
and inferred_dtype in ['boolean', 'date', 'time']):
pytest.xfail(reason='Inferring incorrectly because of NaNs; '
'solved by GH 23167')
if (box == Series
and (dtype == object and inferred_dtype not in [
'string', 'unicode', 'empty',
'bytes', 'mixed', 'mixed-integer'])
or (dtype == 'category'
and inferred_dtype in ['decimal', 'boolean', 'time'])):
pytest.xfail(reason='Not raising correctly; solved by GH 23167')
types_passing_constructor = ['string', 'unicode', 'empty',
'bytes', 'mixed', 'mixed-integer']
if inferred_dtype in types_passing_constructor:
# GH 6106
assert isinstance(t.str, strings.StringMethods)
else:
# GH 9184, GH 23011, GH 23163
with pytest.raises(AttributeError, match='Can only use .str '
'accessor with string values.*'):
t.str
assert not hasattr(t, 'str')
Example #13
| Source File: test_strings.py From recruit with Apache License 2.0 | 5 votes |
|
def test_api(self):
# GH 6106, GH 9322
assert Series.str is strings.StringMethods
assert isinstance(Series(['']).str, strings.StringMethods)
Example #14
| Source File: test_strings.py From recruit with Apache License 2.0 | 5 votes |
|
def any_string_method(request):
"""
Fixture for all public methods of `StringMethods`
This fixture returns a tuple of the method name and sample arguments
necessary to call the method.
Returns
-------
method_name : str
The name of the method in `StringMethods`
args : tuple
Sample values for the positional arguments
kwargs : dict
Sample values for the keyword arguments
Examples
--------
>>> def test_something(any_string_method):
... s = pd.Series(['a', 'b', np.nan, 'd'])
...
... method_name, args, kwargs = any_string_method
... method = getattr(s.str, method_name)
... # will not raise
... method(*args, **kwargs)
"""
return request.param
# subset of the full set from pandas/conftest.py
Example #15
| Source File: test_strings.py From vnpy_crypto with MIT License | 4 votes |
|
def test_index_str_accessor_visibility(self):
from pandas.core.strings import StringMethods
if not compat.PY3:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'mixed'),
([u('a'), u('b')], 'unicode'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
else:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'string'),
([u('a'), u('b')], 'string'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
cases = [([1, np.nan], 'floating'),
([datetime(2011, 1, 1)], 'datetime64'),
([timedelta(1)], 'timedelta64')]
for values, tp in cases:
idx = Index(values)
message = 'Can only use .str accessor with string values'
with tm.assert_raises_regex(AttributeError, message):
Series(values).str
with tm.assert_raises_regex(AttributeError, message):
idx.str
assert idx.inferred_type == tp
# MultiIndex has mixed dtype, but not allow to use accessor
idx = MultiIndex.from_tuples([('a', 'b'), ('a', 'b')])
assert idx.inferred_type == 'mixed'
message = 'Can only use .str accessor with Index, not MultiIndex'
with tm.assert_raises_regex(AttributeError, message):
idx.str
Example #16
| Source File: test_strings.py From elasticintel with GNU General Public License v3.0 | 4 votes |
|
def test_index_str_accessor_visibility(self):
from pandas.core.strings import StringMethods
if not compat.PY3:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'mixed'),
([u('a'), u('b')], 'unicode'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
else:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'string'),
([u('a'), u('b')], 'string'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
cases = [([1, np.nan], 'floating'),
([datetime(2011, 1, 1)], 'datetime64'),
([timedelta(1)], 'timedelta64')]
for values, tp in cases:
idx = Index(values)
message = 'Can only use .str accessor with string values'
with tm.assert_raises_regex(AttributeError, message):
Series(values).str
with tm.assert_raises_regex(AttributeError, message):
idx.str
assert idx.inferred_type == tp
# MultiIndex has mixed dtype, but not allow to use accessor
idx = MultiIndex.from_tuples([('a', 'b'), ('a', 'b')])
assert idx.inferred_type == 'mixed'
message = 'Can only use .str accessor with Index, not MultiIndex'
with tm.assert_raises_regex(AttributeError, message):
idx.str
Example #17
| Source File: test_strings.py From twitter-stock-recommendation with MIT License | 4 votes |
|
def test_index_str_accessor_visibility(self):
from pandas.core.strings import StringMethods
if not compat.PY3:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'mixed'),
([u('a'), u('b')], 'unicode'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
else:
cases = [(['a', 'b'], 'string'), (['a', u('b')], 'string'),
([u('a'), u('b')], 'string'),
(['a', 'b', 1], 'mixed-integer'),
(['a', 'b', 1.3], 'mixed'),
(['a', 'b', 1.3, 1], 'mixed-integer'),
(['aa', datetime(2011, 1, 1)], 'mixed')]
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
for values, tp in cases:
idx = Index(values)
assert isinstance(Series(values).str, StringMethods)
assert isinstance(idx.str, StringMethods)
assert idx.inferred_type == tp
cases = [([1, np.nan], 'floating'),
([datetime(2011, 1, 1)], 'datetime64'),
([timedelta(1)], 'timedelta64')]
for values, tp in cases:
idx = Index(values)
message = 'Can only use .str accessor with string values'
with tm.assert_raises_regex(AttributeError, message):
Series(values).str
with tm.assert_raises_regex(AttributeError, message):
idx.str
assert idx.inferred_type == tp
# MultiIndex has mixed dtype, but not allow to use accessor
idx = MultiIndex.from_tuples([('a', 'b'), ('a', 'b')])
assert idx.inferred_type == 'mixed'
message = 'Can only use .str accessor with Index, not MultiIndex'
with tm.assert_raises_regex(AttributeError, message):
idx.str
