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