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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