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Feb 10, 2015
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ENH: Add StringMethods.isnumeric and isdecimal #9439

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2 changes: 2 additions & 0 deletions doc/source/api.rst
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Expand Up @@ -559,6 +559,8 @@ strings and apply several methods to it. These can be acccessed like
Series.str.islower
Series.str.isupper
Series.str.istitle
Series.str.isnumeric
Series.str.isdecimal
Series.str.get_dummies

.. _api.categorical:
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2 changes: 2 additions & 0 deletions doc/source/text.rst
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Expand Up @@ -238,3 +238,5 @@ Method Summary
:meth:`~Series.str.islower`,Equivalent to ``str.islower``
:meth:`~Series.str.isupper`,Equivalent to ``str.isupper``
:meth:`~Series.str.istitle`,Equivalent to ``str.istitle``
:meth:`~Series.str.isnumeric`,Equivalent to ``str.isnumeric``
:meth:`~Series.str.isnumeric`,Equivalent to ``str.isdecimal``
2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.16.0.txt
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Expand Up @@ -157,7 +157,7 @@ Enhancements
``isupper()``, ``istitle()`` which behave as the same as standard ``str`` (:issue:`9282`)



- Added ``StringMethods.isnumeric`` and ``isdecimal`` which behave as the same as standard ``str`` (:issue:`9439`)
- Added ``StringMethods.ljust()`` and ``rjust()`` which behave as the same as standard ``str`` (:issue:`9352`)
- ``StringMethods.pad()`` and ``center()`` now accept ``fillchar`` option to specify filling character (:issue:`9352`)
- Added ``StringMethods.zfill()`` which behave as the same as standard ``str`` (:issue:`9387`)
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30 changes: 22 additions & 8 deletions pandas/core/strings.py
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Expand Up @@ -1096,23 +1096,37 @@ def get_dummies(self, sep='|'):
docstring=_shared_docs['casemethods'] % 'titlecase')

_shared_docs['ismethods'] = ("""
Check whether all characters in each string in the array are %s
Check whether all characters in each string in the array are %(type)s.
Equivalent to ``str.%(method)s``.

Returns
-------
Series of boolean values
""")
_shared_docs['isalnum'] = dict(type='alphanumeric', method='isalnum')
_shared_docs['isalpha'] = dict(type='alphabetic', method='isalpha')
_shared_docs['isdigit'] = dict(type='digits', method='isdigit')
_shared_docs['isspace'] = dict(type='whitespace', method='isspace')
_shared_docs['islower'] = dict(type='lowercase', method='islower')
_shared_docs['isupper'] = dict(type='uppercase', method='isupper')
_shared_docs['istitle'] = dict(type='titlecase', method='istitle')
_shared_docs['isnumeric'] = dict(type='numeric', method='isnumeric')
_shared_docs['isdecimal'] = dict(type='decimal', method='isdecimal')
isalnum = _noarg_wrapper(lambda x: x.isalnum(),
docstring=_shared_docs['ismethods'] % 'alphanumeric')
docstring=_shared_docs['ismethods'] % _shared_docs['isalnum'])
isalpha = _noarg_wrapper(lambda x: x.isalpha(),
docstring=_shared_docs['ismethods'] % 'alphabetic')
docstring=_shared_docs['ismethods'] % _shared_docs['isalpha'])
isdigit = _noarg_wrapper(lambda x: x.isdigit(),
docstring=_shared_docs['ismethods'] % 'digits')
docstring=_shared_docs['ismethods'] % _shared_docs['isdigit'])
isspace = _noarg_wrapper(lambda x: x.isspace(),
docstring=_shared_docs['ismethods'] % 'whitespace')
docstring=_shared_docs['ismethods'] % _shared_docs['isspace'])
islower = _noarg_wrapper(lambda x: x.islower(),
docstring=_shared_docs['ismethods'] % 'lowercase')
docstring=_shared_docs['ismethods'] % _shared_docs['islower'])
isupper = _noarg_wrapper(lambda x: x.isupper(),
docstring=_shared_docs['ismethods'] % 'uppercase')
docstring=_shared_docs['ismethods'] % _shared_docs['isupper'])
istitle = _noarg_wrapper(lambda x: x.istitle(),
docstring=_shared_docs['ismethods'] % 'titlecase')
docstring=_shared_docs['ismethods'] % _shared_docs['istitle'])
isnumeric = _noarg_wrapper(lambda x: compat.u_safe(x).isnumeric(),
docstring=_shared_docs['ismethods'] % _shared_docs['isnumeric'])
isdecimal = _noarg_wrapper(lambda x: compat.u_safe(x).isdecimal(),
docstring=_shared_docs['ismethods'] % _shared_docs['isdecimal'])
29 changes: 28 additions & 1 deletion pandas/tests/test_strings.py
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Expand Up @@ -14,7 +14,7 @@
from numpy.testing import assert_array_equal
from numpy.random import randint

from pandas.compat import range, lrange, u
from pandas.compat import range, lrange, u, unichr
import pandas.compat as compat
from pandas import (Index, Series, TimeSeries, DataFrame, isnull, notnull,
bdate_range, date_range, MultiIndex)
Expand Down Expand Up @@ -630,6 +630,8 @@ def test_empty_str_methods(self):
tm.assert_series_equal(empty_str, empty.str.islower())
tm.assert_series_equal(empty_str, empty.str.isupper())
tm.assert_series_equal(empty_str, empty.str.istitle())
tm.assert_series_equal(empty_str, empty.str.isnumeric())
tm.assert_series_equal(empty_str, empty.str.isdecimal())

def test_ismethods(self):
values = ['A', 'b', 'Xy', '4', '3A', '', 'TT', '55', '-', ' ']
Expand Down Expand Up @@ -659,6 +661,31 @@ def test_ismethods(self):
self.assertEquals(str_s.str.isupper().tolist(), [v.isupper() for v in values])
self.assertEquals(str_s.str.istitle().tolist(), [v.istitle() for v in values])

def test_isnumeric(self):
# 0x00bc: ¼ VULGAR FRACTION ONE QUARTER
# 0x2605: ★ not number
# 0x1378: ፸ ETHIOPIC NUMBER SEVENTY
# 0xFF13: ３ Em 3
values = ['A', '3', unichr(0x00bc), unichr(0x2605),
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ugh... I guess we still support Python 3.2 :(

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Isn't 3.2 tested in below? I've expected compat.unichr can work for 3.2 also.

https://travis-ci.org/pydata/pandas/jobs/49806158

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I know, it works!

I was going to suggest just using u'¼' but the u unicode literal is not supported on Python 3.2.

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I see. I also tried to use u at first and failed... Will wait a conclusion of #9118.

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u(...) is the way to handle 3.2 compat

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I think we can't use u( ) here because escaped unicode is not handled as numeric or decimal.

unichr(0x1378), unichr(0xFF13), 'four']
s = Series(values)
numeric_e = [False, True, True, False, True, True, False]
decimal_e = [False, True, False, False, False, True, False]
tm.assert_series_equal(s.str.isnumeric(), Series(numeric_e))
tm.assert_series_equal(s.str.isdecimal(), Series(decimal_e))
unicodes = [u('A'), u('3'), unichr(0x00bc), unichr(0x2605),
unichr(0x1378), unichr(0xFF13), u('four')]
self.assertEquals(s.str.isnumeric().tolist(), [v.isnumeric() for v in unicodes])
self.assertEquals(s.str.isdecimal().tolist(), [v.isdecimal() for v in unicodes])

values = ['A', np.nan, unichr(0x00bc), unichr(0x2605),
np.nan, unichr(0xFF13), 'four']
s = Series(values)
numeric_e = [False, np.nan, True, False, np.nan, True, False]
decimal_e = [False, np.nan, False, False, np.nan, True, False]
tm.assert_series_equal(s.str.isnumeric(), Series(numeric_e))
tm.assert_series_equal(s.str.isdecimal(), Series(decimal_e))

def test_get_dummies(self):
s = Series(['a|b', 'a|c', np.nan])
result = s.str.get_dummies('|')
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