You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
144 lines
4.5 KiB
144 lines
4.5 KiB
import pytest
|
|
|
|
from pandas import (
|
|
DataFrame,
|
|
Index,
|
|
MultiIndex,
|
|
Series,
|
|
_testing as tm,
|
|
)
|
|
from pandas.core.strings.accessor import StringMethods
|
|
|
|
|
|
def test_api(any_string_dtype):
|
|
# GH 6106, GH 9322
|
|
assert Series.str is StringMethods
|
|
assert isinstance(Series([""], dtype=any_string_dtype).str, StringMethods)
|
|
|
|
|
|
def test_api_mi_raises():
|
|
# GH 23679
|
|
mi = MultiIndex.from_arrays([["a", "b", "c"]])
|
|
msg = "Can only use .str accessor with Index, not MultiIndex"
|
|
with pytest.raises(AttributeError, match=msg):
|
|
mi.str
|
|
assert not hasattr(mi, "str")
|
|
|
|
|
|
@pytest.mark.parametrize("dtype", [object, "category"])
|
|
def test_api_per_dtype(index_or_series, dtype, any_skipna_inferred_dtype):
|
|
# one instance of parametrized fixture
|
|
box = index_or_series
|
|
inferred_dtype, values = any_skipna_inferred_dtype
|
|
|
|
t = box(values, dtype=dtype) # explicit dtype to avoid casting
|
|
|
|
types_passing_constructor = [
|
|
"string",
|
|
"unicode",
|
|
"empty",
|
|
"bytes",
|
|
"mixed",
|
|
"mixed-integer",
|
|
]
|
|
if inferred_dtype in types_passing_constructor:
|
|
# GH 6106
|
|
assert isinstance(t.str, StringMethods)
|
|
else:
|
|
# GH 9184, GH 23011, GH 23163
|
|
msg = "Can only use .str accessor with string values.*"
|
|
with pytest.raises(AttributeError, match=msg):
|
|
t.str
|
|
assert not hasattr(t, "str")
|
|
|
|
|
|
@pytest.mark.parametrize("dtype", [object, "category"])
|
|
def test_api_per_method(
|
|
index_or_series,
|
|
dtype,
|
|
any_allowed_skipna_inferred_dtype,
|
|
any_string_method,
|
|
request,
|
|
):
|
|
# this test does not check correctness of the different methods,
|
|
# just that the methods work on the specified (inferred) dtypes,
|
|
# and raise on all others
|
|
box = index_or_series
|
|
|
|
# one instance of each parametrized fixture
|
|
inferred_dtype, values = any_allowed_skipna_inferred_dtype
|
|
method_name, args, kwargs = any_string_method
|
|
|
|
reason = None
|
|
if box is Index and values.size == 0:
|
|
if method_name in ["partition", "rpartition"] and kwargs.get("expand", True):
|
|
raises = TypeError
|
|
reason = "Method cannot deal with empty Index"
|
|
elif method_name == "split" and kwargs.get("expand", None):
|
|
raises = TypeError
|
|
reason = "Split fails on empty Series when expand=True"
|
|
elif method_name == "get_dummies":
|
|
raises = ValueError
|
|
reason = "Need to fortify get_dummies corner cases"
|
|
|
|
elif (
|
|
box is Index
|
|
and inferred_dtype == "empty"
|
|
and dtype == object
|
|
and method_name == "get_dummies"
|
|
):
|
|
raises = ValueError
|
|
reason = "Need to fortify get_dummies corner cases"
|
|
|
|
if reason is not None:
|
|
mark = pytest.mark.xfail(raises=raises, reason=reason)
|
|
request.node.add_marker(mark)
|
|
|
|
t = box(values, dtype=dtype) # explicit dtype to avoid casting
|
|
method = getattr(t.str, method_name)
|
|
|
|
bytes_allowed = method_name in ["decode", "get", "len", "slice"]
|
|
# as of v0.23.4, all methods except 'cat' are very lenient with the
|
|
# allowed data types, just returning NaN for entries that error.
|
|
# This could be changed with an 'errors'-kwarg to the `str`-accessor,
|
|
# see discussion in GH 13877
|
|
mixed_allowed = method_name not in ["cat"]
|
|
|
|
allowed_types = (
|
|
["string", "unicode", "empty"]
|
|
+ ["bytes"] * bytes_allowed
|
|
+ ["mixed", "mixed-integer"] * mixed_allowed
|
|
)
|
|
|
|
if inferred_dtype in allowed_types:
|
|
# xref GH 23555, GH 23556
|
|
method(*args, **kwargs) # works!
|
|
else:
|
|
# GH 23011, GH 23163
|
|
msg = (
|
|
f"Cannot use .str.{method_name} with values of "
|
|
f"inferred dtype {repr(inferred_dtype)}."
|
|
)
|
|
with pytest.raises(TypeError, match=msg):
|
|
method(*args, **kwargs)
|
|
|
|
|
|
def test_api_for_categorical(any_string_method, any_string_dtype):
|
|
# https://github.com/pandas-dev/pandas/issues/10661
|
|
s = Series(list("aabb"), dtype=any_string_dtype)
|
|
s = s + " " + s
|
|
c = s.astype("category")
|
|
assert isinstance(c.str, StringMethods)
|
|
|
|
method_name, args, kwargs = any_string_method
|
|
|
|
result = getattr(c.str, method_name)(*args, **kwargs)
|
|
expected = getattr(s.astype("object").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
|
|
|