721 lines
25 KiB
Python
721 lines
25 KiB
Python
from datetime import (
|
||
datetime,
|
||
timedelta,
|
||
)
|
||
|
||
import numpy as np
|
||
import pytest
|
||
|
||
from pandas import (
|
||
DataFrame,
|
||
Index,
|
||
MultiIndex,
|
||
Series,
|
||
)
|
||
import pandas._testing as tm
|
||
from pandas.core.strings.accessor import StringMethods
|
||
from pandas.tests.strings import object_pyarrow_numpy
|
||
|
||
|
||
@pytest.mark.parametrize("pattern", [0, True, Series(["foo", "bar"])])
|
||
def test_startswith_endswith_non_str_patterns(pattern):
|
||
# GH3485
|
||
ser = Series(["foo", "bar"])
|
||
msg = f"expected a string or tuple, not {type(pattern).__name__}"
|
||
with pytest.raises(TypeError, match=msg):
|
||
ser.str.startswith(pattern)
|
||
with pytest.raises(TypeError, match=msg):
|
||
ser.str.endswith(pattern)
|
||
|
||
|
||
def test_iter_raises():
|
||
# GH 54173
|
||
ser = Series(["foo", "bar"])
|
||
with pytest.raises(TypeError, match="'StringMethods' object is not iterable"):
|
||
iter(ser.str)
|
||
|
||
|
||
# test integer/float dtypes (inferred by constructor) and mixed
|
||
|
||
|
||
def test_count(any_string_dtype):
|
||
ser = Series(["foo", "foofoo", np.nan, "foooofooofommmfoo"], dtype=any_string_dtype)
|
||
result = ser.str.count("f[o]+")
|
||
expected_dtype = np.float64 if any_string_dtype in object_pyarrow_numpy else "Int64"
|
||
expected = Series([1, 2, np.nan, 4], dtype=expected_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_count_mixed_object():
|
||
ser = Series(
|
||
["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0],
|
||
dtype=object,
|
||
)
|
||
result = ser.str.count("a")
|
||
expected = Series([1, np.nan, 0, np.nan, np.nan, 0, np.nan, np.nan, np.nan])
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_repeat(any_string_dtype):
|
||
ser = Series(["a", "b", np.nan, "c", np.nan, "d"], dtype=any_string_dtype)
|
||
|
||
result = ser.str.repeat(3)
|
||
expected = Series(
|
||
["aaa", "bbb", np.nan, "ccc", np.nan, "ddd"], dtype=any_string_dtype
|
||
)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
result = ser.str.repeat([1, 2, 3, 4, 5, 6])
|
||
expected = Series(
|
||
["a", "bb", np.nan, "cccc", np.nan, "dddddd"], dtype=any_string_dtype
|
||
)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_repeat_mixed_object():
|
||
ser = Series(["a", np.nan, "b", True, datetime.today(), "foo", None, 1, 2.0])
|
||
result = ser.str.repeat(3)
|
||
expected = Series(
|
||
["aaa", np.nan, "bbb", np.nan, np.nan, "foofoofoo", None, np.nan, np.nan],
|
||
dtype=object,
|
||
)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize("arg, repeat", [[None, 4], ["b", None]])
|
||
def test_repeat_with_null(any_string_dtype, arg, repeat):
|
||
# GH: 31632
|
||
ser = Series(["a", arg], dtype=any_string_dtype)
|
||
result = ser.str.repeat([3, repeat])
|
||
expected = Series(["aaa", None], dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_empty_str_methods(any_string_dtype):
|
||
empty_str = empty = Series(dtype=any_string_dtype)
|
||
if any_string_dtype in object_pyarrow_numpy:
|
||
empty_int = Series(dtype="int64")
|
||
empty_bool = Series(dtype=bool)
|
||
else:
|
||
empty_int = Series(dtype="Int64")
|
||
empty_bool = Series(dtype="boolean")
|
||
empty_object = Series(dtype=object)
|
||
empty_bytes = Series(dtype=object)
|
||
empty_df = DataFrame()
|
||
|
||
# GH7241
|
||
# (extract) on empty series
|
||
|
||
tm.assert_series_equal(empty_str, empty.str.cat(empty))
|
||
assert "" == empty.str.cat()
|
||
tm.assert_series_equal(empty_str, empty.str.title())
|
||
tm.assert_series_equal(empty_int, empty.str.count("a"))
|
||
tm.assert_series_equal(empty_bool, empty.str.contains("a"))
|
||
tm.assert_series_equal(empty_bool, empty.str.startswith("a"))
|
||
tm.assert_series_equal(empty_bool, empty.str.endswith("a"))
|
||
tm.assert_series_equal(empty_str, empty.str.lower())
|
||
tm.assert_series_equal(empty_str, empty.str.upper())
|
||
tm.assert_series_equal(empty_str, empty.str.replace("a", "b"))
|
||
tm.assert_series_equal(empty_str, empty.str.repeat(3))
|
||
tm.assert_series_equal(empty_bool, empty.str.match("^a"))
|
||
tm.assert_frame_equal(
|
||
DataFrame(columns=[0], dtype=any_string_dtype),
|
||
empty.str.extract("()", expand=True),
|
||
)
|
||
tm.assert_frame_equal(
|
||
DataFrame(columns=[0, 1], dtype=any_string_dtype),
|
||
empty.str.extract("()()", expand=True),
|
||
)
|
||
tm.assert_series_equal(empty_str, empty.str.extract("()", expand=False))
|
||
tm.assert_frame_equal(
|
||
DataFrame(columns=[0, 1], dtype=any_string_dtype),
|
||
empty.str.extract("()()", expand=False),
|
||
)
|
||
tm.assert_frame_equal(empty_df.set_axis([], axis=1), empty.str.get_dummies())
|
||
tm.assert_series_equal(empty_str, empty_str.str.join(""))
|
||
tm.assert_series_equal(empty_int, empty.str.len())
|
||
tm.assert_series_equal(empty_object, empty_str.str.findall("a"))
|
||
tm.assert_series_equal(empty_int, empty.str.find("a"))
|
||
tm.assert_series_equal(empty_int, empty.str.rfind("a"))
|
||
tm.assert_series_equal(empty_str, empty.str.pad(42))
|
||
tm.assert_series_equal(empty_str, empty.str.center(42))
|
||
tm.assert_series_equal(empty_object, empty.str.split("a"))
|
||
tm.assert_series_equal(empty_object, empty.str.rsplit("a"))
|
||
tm.assert_series_equal(empty_object, empty.str.partition("a", expand=False))
|
||
tm.assert_frame_equal(empty_df, empty.str.partition("a"))
|
||
tm.assert_series_equal(empty_object, empty.str.rpartition("a", expand=False))
|
||
tm.assert_frame_equal(empty_df, empty.str.rpartition("a"))
|
||
tm.assert_series_equal(empty_str, empty.str.slice(stop=1))
|
||
tm.assert_series_equal(empty_str, empty.str.slice(step=1))
|
||
tm.assert_series_equal(empty_str, empty.str.strip())
|
||
tm.assert_series_equal(empty_str, empty.str.lstrip())
|
||
tm.assert_series_equal(empty_str, empty.str.rstrip())
|
||
tm.assert_series_equal(empty_str, empty.str.wrap(42))
|
||
tm.assert_series_equal(empty_str, empty.str.get(0))
|
||
tm.assert_series_equal(empty_object, empty_bytes.str.decode("ascii"))
|
||
tm.assert_series_equal(empty_bytes, empty.str.encode("ascii"))
|
||
# ismethods should always return boolean (GH 29624)
|
||
tm.assert_series_equal(empty_bool, empty.str.isalnum())
|
||
tm.assert_series_equal(empty_bool, empty.str.isalpha())
|
||
tm.assert_series_equal(empty_bool, empty.str.isdigit())
|
||
tm.assert_series_equal(empty_bool, empty.str.isspace())
|
||
tm.assert_series_equal(empty_bool, empty.str.islower())
|
||
tm.assert_series_equal(empty_bool, empty.str.isupper())
|
||
tm.assert_series_equal(empty_bool, empty.str.istitle())
|
||
tm.assert_series_equal(empty_bool, empty.str.isnumeric())
|
||
tm.assert_series_equal(empty_bool, empty.str.isdecimal())
|
||
tm.assert_series_equal(empty_str, empty.str.capitalize())
|
||
tm.assert_series_equal(empty_str, empty.str.swapcase())
|
||
tm.assert_series_equal(empty_str, empty.str.normalize("NFC"))
|
||
|
||
table = str.maketrans("a", "b")
|
||
tm.assert_series_equal(empty_str, empty.str.translate(table))
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, expected",
|
||
[
|
||
("isalnum", [True, True, True, True, True, False, True, True, False, False]),
|
||
("isalpha", [True, True, True, False, False, False, True, False, False, False]),
|
||
(
|
||
"isdigit",
|
||
[False, False, False, True, False, False, False, True, False, False],
|
||
),
|
||
(
|
||
"isnumeric",
|
||
[False, False, False, True, False, False, False, True, False, False],
|
||
),
|
||
(
|
||
"isspace",
|
||
[False, False, False, False, False, False, False, False, False, True],
|
||
),
|
||
(
|
||
"islower",
|
||
[False, True, False, False, False, False, False, False, False, False],
|
||
),
|
||
(
|
||
"isupper",
|
||
[True, False, False, False, True, False, True, False, False, False],
|
||
),
|
||
(
|
||
"istitle",
|
||
[True, False, True, False, True, False, False, False, False, False],
|
||
),
|
||
],
|
||
)
|
||
def test_ismethods(method, expected, any_string_dtype):
|
||
ser = Series(
|
||
["A", "b", "Xy", "4", "3A", "", "TT", "55", "-", " "], dtype=any_string_dtype
|
||
)
|
||
expected_dtype = "bool" if any_string_dtype in object_pyarrow_numpy else "boolean"
|
||
expected = Series(expected, dtype=expected_dtype)
|
||
result = getattr(ser.str, method)()
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
# compare with standard library
|
||
expected = [getattr(item, method)() for item in ser]
|
||
assert list(result) == expected
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, expected",
|
||
[
|
||
("isnumeric", [False, True, True, False, True, True, False]),
|
||
("isdecimal", [False, True, False, False, False, True, False]),
|
||
],
|
||
)
|
||
def test_isnumeric_unicode(method, expected, any_string_dtype):
|
||
# 0x00bc: ¼ VULGAR FRACTION ONE QUARTER
|
||
# 0x2605: ★ not number
|
||
# 0x1378: ፸ ETHIOPIC NUMBER SEVENTY
|
||
# 0xFF13: ３ Em 3 # noqa: RUF003
|
||
ser = Series(
|
||
["A", "3", "¼", "★", "፸", "３", "four"], dtype=any_string_dtype # noqa: RUF001
|
||
)
|
||
expected_dtype = "bool" if any_string_dtype in object_pyarrow_numpy else "boolean"
|
||
expected = Series(expected, dtype=expected_dtype)
|
||
result = getattr(ser.str, method)()
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
# compare with standard library
|
||
expected = [getattr(item, method)() for item in ser]
|
||
assert list(result) == expected
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, expected",
|
||
[
|
||
("isnumeric", [False, np.nan, True, False, np.nan, True, False]),
|
||
("isdecimal", [False, np.nan, False, False, np.nan, True, False]),
|
||
],
|
||
)
|
||
def test_isnumeric_unicode_missing(method, expected, any_string_dtype):
|
||
values = ["A", np.nan, "¼", "★", np.nan, "３", "four"] # noqa: RUF001
|
||
ser = Series(values, dtype=any_string_dtype)
|
||
expected_dtype = "object" if any_string_dtype in object_pyarrow_numpy else "boolean"
|
||
expected = Series(expected, dtype=expected_dtype)
|
||
result = getattr(ser.str, method)()
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_spilt_join_roundtrip(any_string_dtype):
|
||
ser = Series(["a_b_c", "c_d_e", np.nan, "f_g_h"], dtype=any_string_dtype)
|
||
result = ser.str.split("_").str.join("_")
|
||
expected = ser.astype(object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_spilt_join_roundtrip_mixed_object():
|
||
ser = Series(
|
||
["a_b", np.nan, "asdf_cas_asdf", True, datetime.today(), "foo", None, 1, 2.0]
|
||
)
|
||
result = ser.str.split("_").str.join("_")
|
||
expected = Series(
|
||
["a_b", np.nan, "asdf_cas_asdf", np.nan, np.nan, "foo", None, np.nan, np.nan],
|
||
dtype=object,
|
||
)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_len(any_string_dtype):
|
||
ser = Series(
|
||
["foo", "fooo", "fooooo", np.nan, "fooooooo", "foo\n", "あ"],
|
||
dtype=any_string_dtype,
|
||
)
|
||
result = ser.str.len()
|
||
expected_dtype = "float64" if any_string_dtype in object_pyarrow_numpy else "Int64"
|
||
expected = Series([3, 4, 6, np.nan, 8, 4, 1], dtype=expected_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_len_mixed():
|
||
ser = Series(
|
||
["a_b", np.nan, "asdf_cas_asdf", True, datetime.today(), "foo", None, 1, 2.0]
|
||
)
|
||
result = ser.str.len()
|
||
expected = Series([3, np.nan, 13, np.nan, np.nan, 3, np.nan, np.nan, np.nan])
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method,sub,start,end,expected",
|
||
[
|
||
("index", "EF", None, None, [4, 3, 1, 0]),
|
||
("rindex", "EF", None, None, [4, 5, 7, 4]),
|
||
("index", "EF", 3, None, [4, 3, 7, 4]),
|
||
("rindex", "EF", 3, None, [4, 5, 7, 4]),
|
||
("index", "E", 4, 8, [4, 5, 7, 4]),
|
||
("rindex", "E", 0, 5, [4, 3, 1, 4]),
|
||
],
|
||
)
|
||
def test_index(method, sub, start, end, index_or_series, any_string_dtype, expected):
|
||
obj = index_or_series(
|
||
["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF"], dtype=any_string_dtype
|
||
)
|
||
expected_dtype = np.int64 if any_string_dtype in object_pyarrow_numpy else "Int64"
|
||
expected = index_or_series(expected, dtype=expected_dtype)
|
||
|
||
result = getattr(obj.str, method)(sub, start, end)
|
||
|
||
if index_or_series is Series:
|
||
tm.assert_series_equal(result, expected)
|
||
else:
|
||
tm.assert_index_equal(result, expected)
|
||
|
||
# compare with standard library
|
||
expected = [getattr(item, method)(sub, start, end) for item in obj]
|
||
assert list(result) == expected
|
||
|
||
|
||
def test_index_not_found_raises(index_or_series, any_string_dtype):
|
||
obj = index_or_series(
|
||
["ABCDEFG", "BCDEFEF", "DEFGHIJEF", "EFGHEF"], dtype=any_string_dtype
|
||
)
|
||
with pytest.raises(ValueError, match="substring not found"):
|
||
obj.str.index("DE")
|
||
|
||
|
||
@pytest.mark.parametrize("method", ["index", "rindex"])
|
||
def test_index_wrong_type_raises(index_or_series, any_string_dtype, method):
|
||
obj = index_or_series([], dtype=any_string_dtype)
|
||
msg = "expected a string object, not int"
|
||
|
||
with pytest.raises(TypeError, match=msg):
|
||
getattr(obj.str, method)(0)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, exp",
|
||
[
|
||
["index", [1, 1, 0]],
|
||
["rindex", [3, 1, 2]],
|
||
],
|
||
)
|
||
def test_index_missing(any_string_dtype, method, exp):
|
||
ser = Series(["abcb", "ab", "bcbe", np.nan], dtype=any_string_dtype)
|
||
expected_dtype = np.float64 if any_string_dtype in object_pyarrow_numpy else "Int64"
|
||
|
||
result = getattr(ser.str, method)("b")
|
||
expected = Series(exp + [np.nan], dtype=expected_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_pipe_failures(any_string_dtype):
|
||
# #2119
|
||
ser = Series(["A|B|C"], dtype=any_string_dtype)
|
||
|
||
result = ser.str.split("|")
|
||
expected = Series([["A", "B", "C"]], dtype=object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
result = ser.str.replace("|", " ", regex=False)
|
||
expected = Series(["A B C"], dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"start, stop, step, expected",
|
||
[
|
||
(2, 5, None, ["foo", "bar", np.nan, "baz"]),
|
||
(0, 3, -1, ["", "", np.nan, ""]),
|
||
(None, None, -1, ["owtoofaa", "owtrabaa", np.nan, "xuqzabaa"]),
|
||
(3, 10, 2, ["oto", "ato", np.nan, "aqx"]),
|
||
(3, 0, -1, ["ofa", "aba", np.nan, "aba"]),
|
||
],
|
||
)
|
||
def test_slice(start, stop, step, expected, any_string_dtype):
|
||
ser = Series(["aafootwo", "aabartwo", np.nan, "aabazqux"], dtype=any_string_dtype)
|
||
result = ser.str.slice(start, stop, step)
|
||
expected = Series(expected, dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"start, stop, step, expected",
|
||
[
|
||
(2, 5, None, ["foo", np.nan, "bar", np.nan, np.nan, None, np.nan, np.nan]),
|
||
(4, 1, -1, ["oof", np.nan, "rab", np.nan, np.nan, None, np.nan, np.nan]),
|
||
],
|
||
)
|
||
def test_slice_mixed_object(start, stop, step, expected):
|
||
ser = Series(["aafootwo", np.nan, "aabartwo", True, datetime.today(), None, 1, 2.0])
|
||
result = ser.str.slice(start, stop, step)
|
||
expected = Series(expected, dtype=object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"start,stop,repl,expected",
|
||
[
|
||
(2, 3, None, ["shrt", "a it longer", "evnlongerthanthat", "", np.nan]),
|
||
(2, 3, "z", ["shzrt", "a zit longer", "evznlongerthanthat", "z", np.nan]),
|
||
(2, 2, "z", ["shzort", "a zbit longer", "evzenlongerthanthat", "z", np.nan]),
|
||
(2, 1, "z", ["shzort", "a zbit longer", "evzenlongerthanthat", "z", np.nan]),
|
||
(-1, None, "z", ["shorz", "a bit longez", "evenlongerthanthaz", "z", np.nan]),
|
||
(None, -2, "z", ["zrt", "zer", "zat", "z", np.nan]),
|
||
(6, 8, "z", ["shortz", "a bit znger", "evenlozerthanthat", "z", np.nan]),
|
||
(-10, 3, "z", ["zrt", "a zit longer", "evenlongzerthanthat", "z", np.nan]),
|
||
],
|
||
)
|
||
def test_slice_replace(start, stop, repl, expected, any_string_dtype):
|
||
ser = Series(
|
||
["short", "a bit longer", "evenlongerthanthat", "", np.nan],
|
||
dtype=any_string_dtype,
|
||
)
|
||
expected = Series(expected, dtype=any_string_dtype)
|
||
result = ser.str.slice_replace(start, stop, repl)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, exp",
|
||
[
|
||
["strip", ["aa", "bb", np.nan, "cc"]],
|
||
["lstrip", ["aa ", "bb \n", np.nan, "cc "]],
|
||
["rstrip", [" aa", " bb", np.nan, "cc"]],
|
||
],
|
||
)
|
||
def test_strip_lstrip_rstrip(any_string_dtype, method, exp):
|
||
ser = Series([" aa ", " bb \n", np.nan, "cc "], dtype=any_string_dtype)
|
||
|
||
result = getattr(ser.str, method)()
|
||
expected = Series(exp, dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, exp",
|
||
[
|
||
["strip", ["aa", np.nan, "bb"]],
|
||
["lstrip", ["aa ", np.nan, "bb \t\n"]],
|
||
["rstrip", [" aa", np.nan, " bb"]],
|
||
],
|
||
)
|
||
def test_strip_lstrip_rstrip_mixed_object(method, exp):
|
||
ser = Series([" aa ", np.nan, " bb \t\n", True, datetime.today(), None, 1, 2.0])
|
||
|
||
result = getattr(ser.str, method)()
|
||
expected = Series(exp + [np.nan, np.nan, None, np.nan, np.nan], dtype=object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"method, exp",
|
||
[
|
||
["strip", ["ABC", " BNSD", "LDFJH "]],
|
||
["lstrip", ["ABCxx", " BNSD", "LDFJH xx"]],
|
||
["rstrip", ["xxABC", "xx BNSD", "LDFJH "]],
|
||
],
|
||
)
|
||
def test_strip_lstrip_rstrip_args(any_string_dtype, method, exp):
|
||
ser = Series(["xxABCxx", "xx BNSD", "LDFJH xx"], dtype=any_string_dtype)
|
||
|
||
result = getattr(ser.str, method)("x")
|
||
expected = Series(exp, dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"prefix, expected", [("a", ["b", " b c", "bc"]), ("ab", ["", "a b c", "bc"])]
|
||
)
|
||
def test_removeprefix(any_string_dtype, prefix, expected):
|
||
ser = Series(["ab", "a b c", "bc"], dtype=any_string_dtype)
|
||
result = ser.str.removeprefix(prefix)
|
||
ser_expected = Series(expected, dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, ser_expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"suffix, expected", [("c", ["ab", "a b ", "b"]), ("bc", ["ab", "a b c", ""])]
|
||
)
|
||
def test_removesuffix(any_string_dtype, suffix, expected):
|
||
ser = Series(["ab", "a b c", "bc"], dtype=any_string_dtype)
|
||
result = ser.str.removesuffix(suffix)
|
||
ser_expected = Series(expected, dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, ser_expected)
|
||
|
||
|
||
def test_string_slice_get_syntax(any_string_dtype):
|
||
ser = Series(
|
||
["YYY", "B", "C", "YYYYYYbYYY", "BYYYcYYY", np.nan, "CYYYBYYY", "dog", "cYYYt"],
|
||
dtype=any_string_dtype,
|
||
)
|
||
|
||
result = ser.str[0]
|
||
expected = ser.str.get(0)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
result = ser.str[:3]
|
||
expected = ser.str.slice(stop=3)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
result = ser.str[2::-1]
|
||
expected = ser.str.slice(start=2, step=-1)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_string_slice_out_of_bounds_nested():
|
||
ser = Series([(1, 2), (1,), (3, 4, 5)])
|
||
result = ser.str[1]
|
||
expected = Series([2, np.nan, 4])
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_string_slice_out_of_bounds(any_string_dtype):
|
||
ser = Series(["foo", "b", "ba"], dtype=any_string_dtype)
|
||
result = ser.str[1]
|
||
expected = Series(["o", np.nan, "a"], dtype=any_string_dtype)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_encode_decode(any_string_dtype):
|
||
ser = Series(["a", "b", "a\xe4"], dtype=any_string_dtype).str.encode("utf-8")
|
||
result = ser.str.decode("utf-8")
|
||
expected = ser.map(lambda x: x.decode("utf-8")).astype(object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_encode_errors_kwarg(any_string_dtype):
|
||
ser = Series(["a", "b", "a\x9d"], dtype=any_string_dtype)
|
||
|
||
msg = (
|
||
r"'charmap' codec can't encode character '\\x9d' in position 1: "
|
||
"character maps to <undefined>"
|
||
)
|
||
with pytest.raises(UnicodeEncodeError, match=msg):
|
||
ser.str.encode("cp1252")
|
||
|
||
result = ser.str.encode("cp1252", "ignore")
|
||
expected = ser.map(lambda x: x.encode("cp1252", "ignore"))
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_decode_errors_kwarg():
|
||
ser = Series([b"a", b"b", b"a\x9d"])
|
||
|
||
msg = (
|
||
"'charmap' codec can't decode byte 0x9d in position 1: "
|
||
"character maps to <undefined>"
|
||
)
|
||
with pytest.raises(UnicodeDecodeError, match=msg):
|
||
ser.str.decode("cp1252")
|
||
|
||
result = ser.str.decode("cp1252", "ignore")
|
||
expected = ser.map(lambda x: x.decode("cp1252", "ignore")).astype(object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"form, expected",
|
||
[
|
||
("NFKC", ["ABC", "ABC", "123", np.nan, "アイエ"]),
|
||
("NFC", ["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"]), # noqa: RUF001
|
||
],
|
||
)
|
||
def test_normalize(form, expected, any_string_dtype):
|
||
ser = Series(
|
||
["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"], # noqa: RUF001
|
||
index=["a", "b", "c", "d", "e"],
|
||
dtype=any_string_dtype,
|
||
)
|
||
expected = Series(expected, index=["a", "b", "c", "d", "e"], dtype=any_string_dtype)
|
||
result = ser.str.normalize(form)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_normalize_bad_arg_raises(any_string_dtype):
|
||
ser = Series(
|
||
["ABC", "ＡＢＣ", "１２３", np.nan, "ｱｲｴ"], # noqa: RUF001
|
||
index=["a", "b", "c", "d", "e"],
|
||
dtype=any_string_dtype,
|
||
)
|
||
with pytest.raises(ValueError, match="invalid normalization form"):
|
||
ser.str.normalize("xxx")
|
||
|
||
|
||
def test_normalize_index():
|
||
idx = Index(["ＡＢＣ", "１２３", "ｱｲｴ"]) # noqa: RUF001
|
||
expected = Index(["ABC", "123", "アイエ"])
|
||
result = idx.str.normalize("NFKC")
|
||
tm.assert_index_equal(result, expected)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"values,inferred_type",
|
||
[
|
||
(["a", "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"),
|
||
],
|
||
)
|
||
def test_index_str_accessor_visibility(values, inferred_type, index_or_series):
|
||
obj = index_or_series(values)
|
||
if index_or_series is Index:
|
||
assert obj.inferred_type == inferred_type
|
||
|
||
assert isinstance(obj.str, StringMethods)
|
||
|
||
|
||
@pytest.mark.parametrize(
|
||
"values,inferred_type",
|
||
[
|
||
([1, np.nan], "floating"),
|
||
([datetime(2011, 1, 1)], "datetime64"),
|
||
([timedelta(1)], "timedelta64"),
|
||
],
|
||
)
|
||
def test_index_str_accessor_non_string_values_raises(
|
||
values, inferred_type, index_or_series
|
||
):
|
||
obj = index_or_series(values)
|
||
if index_or_series is Index:
|
||
assert obj.inferred_type == inferred_type
|
||
|
||
msg = "Can only use .str accessor with string values"
|
||
with pytest.raises(AttributeError, match=msg):
|
||
obj.str
|
||
|
||
|
||
def test_index_str_accessor_multiindex_raises():
|
||
# MultiIndex has mixed dtype, but not allow to use accessor
|
||
idx = MultiIndex.from_tuples([("a", "b"), ("a", "b")])
|
||
assert idx.inferred_type == "mixed"
|
||
|
||
msg = "Can only use .str accessor with Index, not MultiIndex"
|
||
with pytest.raises(AttributeError, match=msg):
|
||
idx.str
|
||
|
||
|
||
def test_str_accessor_no_new_attributes(any_string_dtype):
|
||
# https://github.com/pandas-dev/pandas/issues/10673
|
||
ser = Series(list("aabbcde"), dtype=any_string_dtype)
|
||
with pytest.raises(AttributeError, match="You cannot add any new attribute"):
|
||
ser.str.xlabel = "a"
|
||
|
||
|
||
def test_cat_on_bytes_raises():
|
||
lhs = Series(np.array(list("abc"), "S1").astype(object))
|
||
rhs = Series(np.array(list("def"), "S1").astype(object))
|
||
msg = "Cannot use .str.cat with values of inferred dtype 'bytes'"
|
||
with pytest.raises(TypeError, match=msg):
|
||
lhs.str.cat(rhs)
|
||
|
||
|
||
def test_str_accessor_in_apply_func():
|
||
# https://github.com/pandas-dev/pandas/issues/38979
|
||
df = DataFrame(zip("abc", "def"))
|
||
expected = Series(["A/D", "B/E", "C/F"])
|
||
result = df.apply(lambda f: "/".join(f.str.upper()), axis=1)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_zfill():
|
||
# https://github.com/pandas-dev/pandas/issues/20868
|
||
value = Series(["-1", "1", "1000", 10, np.nan])
|
||
expected = Series(["-01", "001", "1000", np.nan, np.nan], dtype=object)
|
||
tm.assert_series_equal(value.str.zfill(3), expected)
|
||
|
||
value = Series(["-2", "+5"])
|
||
expected = Series(["-0002", "+0005"])
|
||
tm.assert_series_equal(value.str.zfill(5), expected)
|
||
|
||
|
||
def test_zfill_with_non_integer_argument():
|
||
value = Series(["-2", "+5"])
|
||
wid = "a"
|
||
msg = f"width must be of integer type, not {type(wid).__name__}"
|
||
with pytest.raises(TypeError, match=msg):
|
||
value.str.zfill(wid)
|
||
|
||
|
||
def test_zfill_with_leading_sign():
|
||
value = Series(["-cat", "-1", "+dog"])
|
||
expected = Series(["-0cat", "-0001", "+0dog"])
|
||
tm.assert_series_equal(value.str.zfill(5), expected)
|
||
|
||
|
||
def test_get_with_dict_label():
|
||
# GH47911
|
||
s = Series(
|
||
[
|
||
{"name": "Hello", "value": "World"},
|
||
{"name": "Goodbye", "value": "Planet"},
|
||
{"value": "Sea"},
|
||
]
|
||
)
|
||
result = s.str.get("name")
|
||
expected = Series(["Hello", "Goodbye", None], dtype=object)
|
||
tm.assert_series_equal(result, expected)
|
||
result = s.str.get("value")
|
||
expected = Series(["World", "Planet", "Sea"], dtype=object)
|
||
tm.assert_series_equal(result, expected)
|
||
|
||
|
||
def test_series_str_decode():
|
||
# GH 22613
|
||
result = Series([b"x", b"y"]).str.decode(encoding="UTF-8", errors="strict")
|
||
expected = Series(["x", "y"], dtype="object")
|
||
tm.assert_series_equal(result, expected)
|