from warnings import catch_warnings import numpy as np from pandas.core.dtypes import generic as gt import pandas as pd import pandas._testing as tm class TestABCClasses: tuples = [[1, 2, 2], ["red", "blue", "red"]] multi_index = pd.MultiIndex.from_arrays(tuples, names=("number", "color")) datetime_index = pd.to_datetime(["2000/1/1", "2010/1/1"]) timedelta_index = pd.to_timedelta(np.arange(5), unit="s") period_index = pd.period_range("2000/1/1", "2010/1/1/", freq="M") categorical = pd.Categorical([1, 2, 3], categories=[2, 3, 1]) categorical_df = pd.DataFrame({"values": [1, 2, 3]}, index=categorical) df = pd.DataFrame({"names": ["a", "b", "c"]}, index=multi_index) sparse_array = pd.arrays.SparseArray(np.random.randn(10)) datetime_array = pd.core.arrays.DatetimeArray(datetime_index) timedelta_array = pd.core.arrays.TimedeltaArray(timedelta_index) def test_abc_types(self): assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index) assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index) assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index) assert isinstance(self.multi_index, gt.ABCMultiIndex) assert isinstance(self.datetime_index, gt.ABCDatetimeIndex) assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex) assert isinstance(self.period_index, gt.ABCPeriodIndex) assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex) assert isinstance(pd.Index(["a", "b", "c"]), gt.ABCIndexClass) assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass) assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries) assert isinstance(self.df, gt.ABCDataFrame) assert isinstance(self.sparse_array, gt.ABCExtensionArray) assert isinstance(self.categorical, gt.ABCCategorical) assert isinstance(self.datetime_array, gt.ABCDatetimeArray) assert not isinstance(self.datetime_index, gt.ABCDatetimeArray) assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray) assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray) def test_setattr_warnings(): # GH7175 - GOTCHA: You can't use dot notation to add a column... d = { "one": pd.Series([1.0, 2.0, 3.0], index=["a", "b", "c"]), "two": pd.Series([1.0, 2.0, 3.0, 4.0], index=["a", "b", "c", "d"]), } df = pd.DataFrame(d) with catch_warnings(record=True) as w: # successfully add new column # this should not raise a warning df["three"] = df.two + 1 assert len(w) == 0 assert df.three.sum() > df.two.sum() with catch_warnings(record=True) as w: # successfully modify column in place # this should not raise a warning df.one += 1 assert len(w) == 0 assert df.one.iloc[0] == 2 with catch_warnings(record=True) as w: # successfully add an attribute to a series # this should not raise a warning df.two.not_an_index = [1, 2] assert len(w) == 0 with tm.assert_produces_warning(UserWarning): # warn when setting column to nonexistent name df.four = df.two + 2 assert df.four.sum() > df.two.sum()