Python Series.str方法代碼示例

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_iter(self):
        # GH3638
        strs = 'google', 'wikimedia', 'wikipedia', 'wikitravel'
        ds = Series(strs)

        for s in ds.str:
            # iter must yield a Series
            assert isinstance(s, Series)

            # indices of each yielded Series should be equal to the index of
            # the original Series
            tm.assert_index_equal(s.index, ds.index)

            for el in s:
                # each element of the series is either a basestring/str or nan
                assert isinstance(el, compat.string_types) or isna(el)

        # desired behavior is to iterate until everything would be nan on the
        # next iter so make sure the last element of the iterator was 'l' in
        # this case since 'wikitravel' is the longest string
        assert s.dropna().values.item() == 'l' 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_str_cat_all_na(self, box, other):
        # GH 24044

        # check that all NaNs in caller / target work
        s = Index(['a', 'b', 'c', 'd'])
        s = s if box == Index else Series(s, index=s)
        t = other([np.nan] * 4, dtype=object)
        # add index of s for alignment
        t = t if other == Index else Series(t, index=s)

        # all-NA target
        if box == Series:
            expected = Series([np.nan] * 4, index=s.index, dtype=object)
        else:  # box == Index
            expected = Index([np.nan] * 4, dtype=object)
        result = s.str.cat(t, join='left')
        assert_series_or_index_equal(result, expected)

        # all-NA caller (only for Series)
        if other == Series:
            expected = Series([np.nan] * 4, dtype=object, index=t.index)
            result = t.str.cat(s, join='left')
            tm.assert_series_equal(result, expected) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_cat_on_filtered_index(self):
        df = DataFrame(index=MultiIndex.from_product(
            [[2011, 2012], [1, 2, 3]], names=['year', 'month']))

        df = df.reset_index()
        df = df[df.month > 1]

        str_year = df.year.astype('str')
        str_month = df.month.astype('str')
        str_both = str_year.str.cat(str_month, sep=' ')

        assert str_both.loc[1] == '2011 2'

        str_multiple = str_year.str.cat([str_month, str_month], sep=' ')

        assert str_multiple.loc[1] == '2011 2 2' 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_contains_for_object_category(self):
        # gh 22158

        # na for category
        values = Series(["a", "b", "c", "a", np.nan], dtype="category")
        result = values.str.contains('a', na=True)
        expected = Series([True, False, False, True, True])
        tm.assert_series_equal(result, expected)

        result = values.str.contains('a', na=False)
        expected = Series([True, False, False, True, False])
        tm.assert_series_equal(result, expected)

        # na for objects
        values = Series(["a", "b", "c", "a", np.nan])
        result = values.str.contains('a', na=True)
        expected = Series([True, False, False, True, True])
        tm.assert_series_equal(result, expected)

        result = values.str.contains('a', na=False)
        expected = Series([True, False, False, True, False])
        tm.assert_series_equal(result, expected) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_title(self):
        values = Series(["FOO", "BAR", NA, "Blah", "blurg"])

        result = values.str.title()
        exp = Series(["Foo", "Bar", NA, "Blah", "Blurg"])
        tm.assert_series_equal(result, exp)

        # mixed
        mixed = Series(["FOO", NA, "bar", True, datetime.today(), "blah", None,
                        1, 2.])
        mixed = mixed.str.title()
        exp = Series(["Foo", NA, "Bar", NA, NA, "Blah", NA, NA, NA])
        tm.assert_almost_equal(mixed, exp)

        # unicode
        values = Series([u("FOO"), NA, u("bar"), u("Blurg")])

        results = values.str.title()
        exp = Series([u("Foo"), NA, u("Bar"), u("Blurg")])

        tm.assert_series_equal(results, exp) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_capitalize(self):
        values = Series(["FOO", "BAR", NA, "Blah", "blurg"])
        result = values.str.capitalize()
        exp = Series(["Foo", "Bar", NA, "Blah", "Blurg"])
        tm.assert_series_equal(result, exp)

        # mixed
        mixed = Series(["FOO", NA, "bar", True, datetime.today(), "blah", None,
                        1, 2.])
        mixed = mixed.str.capitalize()
        exp = Series(["Foo", NA, "Bar", NA, NA, "Blah", NA, NA, NA])
        tm.assert_almost_equal(mixed, exp)

        # unicode
        values = Series([u("FOO"), NA, u("bar"), u("Blurg")])
        results = values.str.capitalize()
        exp = Series([u("Foo"), NA, u("Bar"), u("Blurg")])
        tm.assert_series_equal(results, exp) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_swapcase(self):
        values = Series(["FOO", "BAR", NA, "Blah", "blurg"])
        result = values.str.swapcase()
        exp = Series(["foo", "bar", NA, "bLAH", "BLURG"])
        tm.assert_series_equal(result, exp)

        # mixed
        mixed = Series(["FOO", NA, "bar", True, datetime.today(), "Blah", None,
                        1, 2.])
        mixed = mixed.str.swapcase()
        exp = Series(["foo", NA, "BAR", NA, NA, "bLAH", NA, NA, NA])
        tm.assert_almost_equal(mixed, exp)

        # unicode
        values = Series([u("FOO"), NA, u("bar"), u("Blurg")])
        results = values.str.swapcase()
        exp = Series([u("foo"), NA, u("BAR"), u("bLURG")])
        tm.assert_series_equal(results, exp) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_replace_literal(self):
        # GH16808 literal replace (regex=False vs regex=True)
        values = Series(['f.o', 'foo', NA])
        exp = Series(['bao', 'bao', NA])
        result = values.str.replace('f.', 'ba')
        tm.assert_series_equal(result, exp)

        exp = Series(['bao', 'foo', NA])
        result = values.str.replace('f.', 'ba', regex=False)
        tm.assert_series_equal(result, exp)

        # Cannot do a literal replace if given a callable repl or compiled
        # pattern
        callable_repl = lambda m: m.group(0).swapcase()
        compiled_pat = re.compile('[a-z][A-Z]{2}')

        pytest.raises(ValueError, values.str.replace, 'abc', callable_repl,
                      regex=False)
        pytest.raises(ValueError, values.str.replace, compiled_pat, '',
                      regex=False) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_extractall_stringindex(self):
        s = Series(["a1a2", "b1", "c1"], name='xxx')
        res = s.str.extractall(r"[ab](?P<digit>\d)")
        exp_idx = MultiIndex.from_tuples([(0, 0), (0, 1), (1, 0)],
                                         names=[None, 'match'])
        exp = DataFrame({'digit': ["1", "2", "1"]}, index=exp_idx)
        tm.assert_frame_equal(res, exp)

        # index should return the same result as the default index without name
        # thus index.name doesn't affect to the result
        for idx in [Index(["a1a2", "b1", "c1"]),
                    Index(["a1a2", "b1", "c1"], name='xxx')]:

            res = idx.str.extractall(r"[ab](?P<digit>\d)")
            tm.assert_frame_equal(res, exp)

        s = Series(["a1a2", "b1", "c1"], name='s_name',
                   index=Index(["XX", "yy", "zz"], name='idx_name'))
        res = s.str.extractall(r"[ab](?P<digit>\d)")
        exp_idx = MultiIndex.from_tuples([("XX", 0), ("XX", 1), ("yy", 0)],
                                         names=["idx_name", 'match'])
        exp = DataFrame({'digit': ["1", "2", "1"]}, index=exp_idx)
        tm.assert_frame_equal(res, exp) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_extract_index_one_two_groups(self):
        s = Series(['a3', 'b3', 'd4c2'], index=["A3", "B3", "D4"],
                   name='series_name')
        r = s.index.str.extract(r'([A-Z])', expand=True)
        e = DataFrame(['A', "B", "D"])
        tm.assert_frame_equal(r, e)

        # Prior to v0.18.0, index.str.extract(regex with one group)
        # returned Index. With more than one group, extract raised an
        # error (GH9980). Now extract always returns DataFrame.
        r = s.index.str.extract(
            r'(?P<letter>[A-Z])(?P<digit>[0-9])', expand=True)
        e_list = [
            ("A", "3"),
            ("B", "3"),
            ("D", "4"),
        ]
        e = DataFrame(e_list, columns=["letter", "digit"])
        tm.assert_frame_equal(r, e) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
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', u'¼', u'★', u'፸', u'３', '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', u'¼', u'★', u'፸', u'３', u'four']
        assert s.str.isnumeric().tolist() == [v.isnumeric() for v in unicodes]
        assert s.str.isdecimal().tolist() == [v.isdecimal() for v in unicodes]

        values = ['A', np.nan, u'¼', u'★', np.nan, u'３', '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)) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_get_dummies(self):
        s = Series(['a|b', 'a|c', np.nan])
        result = s.str.get_dummies('|')
        expected = DataFrame([[1, 1, 0], [1, 0, 1], [0, 0, 0]],
                             columns=list('abc'))
        tm.assert_frame_equal(result, expected)

        s = Series(['a;b', 'a', 7])
        result = s.str.get_dummies(';')
        expected = DataFrame([[0, 1, 1], [0, 1, 0], [1, 0, 0]],
                             columns=list('7ab'))
        tm.assert_frame_equal(result, expected)

        # GH9980, GH8028
        idx = Index(['a|b', 'a|c', 'b|c'])
        result = idx.str.get_dummies('|')

        expected = MultiIndex.from_tuples([(1, 1, 0), (1, 0, 1),
                                           (0, 1, 1)], names=('a', 'b', 'c'))
        tm.assert_index_equal(result, expected) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_join(self):
        values = Series(['a_b_c', 'c_d_e', np.nan, 'f_g_h'])
        result = values.str.split('_').str.join('_')
        tm.assert_series_equal(values, result)

        # mixed
        mixed = Series(['a_b', NA, 'asdf_cas_asdf', True, datetime.today(),
                        'foo', None, 1, 2.])

        rs = Series(mixed).str.split('_').str.join('_')
        xp = Series(['a_b', NA, 'asdf_cas_asdf', NA, NA, 'foo', NA, NA, NA])

        assert isinstance(rs, Series)
        tm.assert_almost_equal(rs, xp)

        # unicode
        values = Series([u('a_b_c'), u('c_d_e'), np.nan, u('f_g_h')])
        result = values.str.split('_').str.join('_')
        tm.assert_series_equal(values, result) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_len(self):
        values = Series(['foo', 'fooo', 'fooooo', np.nan, 'fooooooo'])

        result = values.str.len()
        exp = values.map(lambda x: len(x) if notna(x) else NA)
        tm.assert_series_equal(result, exp)

        # mixed
        mixed = Series(['a_b', NA, 'asdf_cas_asdf', True, datetime.today(),
                        'foo', None, 1, 2.])

        rs = Series(mixed).str.len()
        xp = Series([3, NA, 13, NA, NA, 3, NA, NA, NA])

        assert isinstance(rs, Series)
        tm.assert_almost_equal(rs, xp)

        # unicode
        values = Series([u('foo'), u('fooo'), u('fooooo'), np.nan, u(
            'fooooooo')])

        result = values.str.len()
        exp = values.map(lambda x: len(x) if notna(x) else NA)
        tm.assert_series_equal(result, exp) 

# 需要導入模塊: from pandas import Series [as 別名]
# 或者: from pandas.Series import str [as 別名]
def test_findall(self):
        values = Series(['fooBAD__barBAD', NA, 'foo', 'BAD'])

        result = values.str.findall('BAD[_]*')
        exp = Series([['BAD__', 'BAD'], NA, [], ['BAD']])
        tm.assert_almost_equal(result, exp)

        # mixed
        mixed = Series(['fooBAD__barBAD', NA, 'foo', True, datetime.today(),
                        'BAD', None, 1, 2.])

        rs = Series(mixed).str.findall('BAD[_]*')
        xp = Series([['BAD__', 'BAD'], NA, [], NA, NA, ['BAD'], NA, NA, NA])

        assert isinstance(rs, Series)
        tm.assert_almost_equal(rs, xp)

        # unicode
        values = Series([u('fooBAD__barBAD'), NA, u('foo'), u('BAD')])

        result = values.str.findall('BAD[_]*')
        exp = Series([[u('BAD__'), u('BAD')], NA, [], [u('BAD')]])
        tm.assert_almost_equal(result, exp)