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import numpy as np import pytest from pandas import ( Categorical, DataFrame, Index, Series, Timestamp, date_range, period_range, timedelta_range, ) import pandas._testing as tm from pandas.core.arrays.categorical import CategoricalAccessor from pandas.core.indexes.accessors import Properties class TestCatAccessor: @pytest.mark.parametrize( "method", [ lambda x: x.cat.set_categories([1, 2, 3]), lambda x: x.cat.reorder_categories([2, 3, 1], ordered=True), lambda x: x.cat.rename_categories([1, 2, 3]), lambda x: x.cat.remove_unused_categories(), lambda x: x.cat.remove_categories([2]), lambda x: x.cat.add_categories([4]), lambda x: x.cat.as_ordered(), lambda x: x.cat.as_unordered(), ], ) def test_getname_categorical_accessor(self, method): # GH#17509 ser = Series([1, 2, 3], name="A").astype("category") expected = "A" result = method(ser).name assert result == expected def test_cat_accessor(self): ser = Series(Categorical(["a", "b", np.nan, "a"])) tm.assert_index_equal(ser.cat.categories, Index(["a", "b"])) assert not ser.cat.ordered, False exp = Categorical(["a", "b", np.nan, "a"], categories=["b", "a"]) res = ser.cat.set_categories(["b", "a"]) tm.assert_categorical_equal(res.values, exp) ser[:] = "a" ser = ser.cat.remove_unused_categories() tm.assert_index_equal(ser.cat.categories, Index(["a"])) def test_cat_accessor_api(self): # GH#9322 assert Series.cat is CategoricalAccessor ser = Series(list("aabbcde")).astype("category") assert isinstance(ser.cat, CategoricalAccessor) invalid = Series([1]) with pytest.raises(AttributeError, match="only use .cat accessor"): invalid.cat assert not hasattr(invalid, "cat") def test_cat_accessor_no_new_attributes(self): # https://github.com/pandas-dev/pandas/issues/10673 cat = Series(list("aabbcde")).astype("category") with pytest.raises(AttributeError, match="You cannot add any new attribute"): cat.cat.xlabel = "a" def test_categorical_delegations(self): # invalid accessor msg = r"Can only use \.cat accessor with a 'category' dtype" with pytest.raises(AttributeError, match=msg): Series([1, 2, 3]).cat with pytest.raises(AttributeError, match=msg): Series([1, 2, 3]).cat() with pytest.raises(AttributeError, match=msg): Series(["a", "b", "c"]).cat with pytest.raises(AttributeError, match=msg): Series(np.arange(5.0)).cat with pytest.raises(AttributeError, match=msg): Series([Timestamp("20130101")]).cat # Series should delegate calls to '.categories', '.codes', '.ordered' # and the methods '.set_categories()' 'drop_unused_categories()' to the # categorical ser = Series(Categorical(["a", "b", "c", "a"], ordered=True)) exp_categories = Index(["a", "b", "c"]) tm.assert_index_equal(ser.cat.categories, exp_categories) ser = ser.cat.rename_categories([1, 2, 3]) exp_categories = Index([1, 2, 3]) tm.assert_index_equal(ser.cat.categories, exp_categories) exp_codes = Series([0, 1, 2, 0], dtype="int8") tm.assert_series_equal(ser.cat.codes, exp_codes) assert ser.cat.ordered ser = ser.cat.as_unordered() assert not ser.cat.ordered ser = ser.cat.as_ordered() assert ser.cat.ordered # reorder ser = Series(Categorical(["a", "b", "c", "a"], ordered=True)) exp_categories = Index(["c", "b", "a"]) exp_values = np.array(["a", "b", "c", "a"], dtype=np.object_) ser = ser.cat.set_categories(["c", "b", "a"]) tm.assert_index_equal(ser.cat.categories, exp_categories) tm.assert_numpy_array_equal(ser.values.__array__(), exp_values) tm.assert_numpy_array_equal(ser.__array__(), exp_values) # remove unused categories ser = Series(Categorical(["a", "b", "b", "a"], categories=["a", "b", "c"])) exp_categories = Index(["a", "b"]) exp_values = np.array(["a", "b", "b", "a"], dtype=np.object_) ser = ser.cat.remove_unused_categories() tm.assert_index_equal(ser.cat.categories, exp_categories) tm.assert_numpy_array_equal(ser.values.__array__(), exp_values) tm.assert_numpy_array_equal(ser.__array__(), exp_values) # This method is likely to be confused, so test that it raises an error # on wrong inputs: msg = "'Series' object has no attribute 'set_categories'" with pytest.raises(AttributeError, match=msg): ser.set_categories([4, 3, 2, 1]) # right: ser.cat.set_categories([4,3,2,1]) # GH#18862 (let Series.cat.rename_categories take callables) ser = Series(Categorical(["a", "b", "c", "a"], ordered=True)) result = ser.cat.rename_categories(lambda x: x.upper()) expected = Series( Categorical(["A", "B", "C", "A"], categories=["A", "B", "C"], ordered=True) ) tm.assert_series_equal(result, expected) @pytest.mark.parametrize( "idx", [ date_range("1/1/2015", periods=5), date_range("1/1/2015", periods=5, tz="MET"), period_range("1/1/2015", freq="D", periods=5), timedelta_range("1 days", "10 days"), ], ) def test_dt_accessor_api_for_categorical(self, idx): # https://github.com/pandas-dev/pandas/issues/10661 ser = Series(idx) cat = ser.astype("category") # only testing field (like .day) # and bool (is_month_start) attr_names = type(ser._values)._datetimelike_ops assert isinstance(cat.dt, Properties) special_func_defs = [ ("strftime", ("%Y-%m-%d",), {}), ("round", ("D",), {}), ("floor", ("D",), {}), ("ceil", ("D",), {}), ("asfreq", ("D",), {}), ("as_unit", ("s"), {}), ] if idx.dtype == "M8[ns]": # exclude dt64tz since that is already localized and would raise tup = ("tz_localize", ("UTC",), {}) special_func_defs.append(tup) elif idx.dtype.kind == "M": # exclude dt64 since that is not localized so would raise tup = ("tz_convert", ("EST",), {}) special_func_defs.append(tup) _special_func_names = [f[0] for f in special_func_defs] _ignore_names = ["components", "tz_localize", "tz_convert"] func_names = [ fname for fname in dir(ser.dt) if not ( fname.startswith("_") or fname in attr_names or fname in _special_func_names or fname in _ignore_names ) ] func_defs = [(fname, (), {}) for fname in func_names] func_defs.extend( f_def for f_def in special_func_defs if f_def[0] in dir(ser.dt) ) for func, args, kwargs in func_defs: warn_cls = [] if func == "to_period" and getattr(idx, "tz", None) is not None: # dropping TZ warn_cls.append(UserWarning) if func == "to_pydatetime": # deprecated to return Index[object] warn_cls.append(FutureWarning) if warn_cls: warn_cls = tuple(warn_cls) else: warn_cls = None with tm.assert_produces_warning(warn_cls): res = getattr(cat.dt, func)(args, kwargs) exp = getattr(ser.dt, func)(args, **kwargs) tm.assert_equal(res, exp) for attr in attr_names: res = getattr(cat.dt, attr) exp = getattr(ser.dt, attr) tm.assert_equal(res, exp) def test_dt_accessor_api_for_categorical_invalid(self): invalid = Series([1, 2, 3]).astype("category") msg = "Can only use .dt accessor with datetimelike" with pytest.raises(AttributeError, match=msg): invalid.dt assert not hasattr(invalid, "str") def test_set_categories_setitem(self): # GH#43334 df = DataFrame({"Survived": [1, 0, 1], "Sex": [0, 1, 1]}, dtype="category") df["Survived"] = df["Survived"].cat.rename_categories(["No", "Yes"]) df["Sex"] = df["Sex"].cat.rename_categories(["female", "male"]) # values should not be coerced to NaN assert list(df["Sex"]) == ["female", "male", "male"] assert list(df["Survived"]) == ["Yes", "No", "Yes"] df["Sex"] = Categorical(df["Sex"], categories=["female", "male"], ordered=False) df["Survived"] = Categorical( df["Survived"], categories=["No", "Yes"], ordered=False ) # values should not be coerced to NaN assert list(df["Sex"]) == ["female", "male", "male"] assert list(df["Survived"]) == ["Yes", "No", "Yes"] def test_categorical_of_booleans_is_boolean(self): # https://github.com/pandas-dev/pandas/issues/46313 df = DataFrame( {"int_cat": [1, 2, 3], "bool_cat": [True, False, False]}, dtype="category" ) value = df["bool_cat"].cat.categories.dtype expected = np.dtype(np.bool_) assert value is expected

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