707 lines
23 KiB
Python
707 lines
23 KiB
Python
import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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import pandas as pd
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from pandas import DataFrame, Index, MultiIndex, Series
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import pandas._testing as tm
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class TestDataFrameSubclassing:
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def test_frame_subclassing_and_slicing(self):
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# Subclass frame and ensure it returns the right class on slicing it
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# In reference to PR 9632
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class CustomSeries(Series):
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@property
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def _constructor(self):
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return CustomSeries
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def custom_series_function(self):
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return "OK"
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class CustomDataFrame(DataFrame):
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"""
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Subclasses pandas DF, fills DF with simulation results, adds some
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custom plotting functions.
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"""
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def __init__(self, *args, **kw):
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super().__init__(*args, **kw)
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@property
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def _constructor(self):
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return CustomDataFrame
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_constructor_sliced = CustomSeries
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def custom_frame_function(self):
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return "OK"
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data = {"col1": range(10), "col2": range(10)}
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cdf = CustomDataFrame(data)
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# Did we get back our own DF class?
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assert isinstance(cdf, CustomDataFrame)
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# Do we get back our own Series class after selecting a column?
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cdf_series = cdf.col1
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assert isinstance(cdf_series, CustomSeries)
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assert cdf_series.custom_series_function() == "OK"
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# Do we get back our own DF class after slicing row-wise?
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cdf_rows = cdf[1:5]
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assert isinstance(cdf_rows, CustomDataFrame)
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assert cdf_rows.custom_frame_function() == "OK"
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# Make sure sliced part of multi-index frame is custom class
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mcol = pd.MultiIndex.from_tuples([("A", "A"), ("A", "B")])
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cdf_multi = CustomDataFrame([[0, 1], [2, 3]], columns=mcol)
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assert isinstance(cdf_multi["A"], CustomDataFrame)
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mcol = pd.MultiIndex.from_tuples([("A", ""), ("B", "")])
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cdf_multi2 = CustomDataFrame([[0, 1], [2, 3]], columns=mcol)
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assert isinstance(cdf_multi2["A"], CustomSeries)
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def test_dataframe_metadata(self):
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df = tm.SubclassedDataFrame(
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{"X": [1, 2, 3], "Y": [1, 2, 3]}, index=["a", "b", "c"]
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)
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df.testattr = "XXX"
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assert df.testattr == "XXX"
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assert df[["X"]].testattr == "XXX"
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assert df.loc[["a", "b"], :].testattr == "XXX"
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assert df.iloc[[0, 1], :].testattr == "XXX"
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# see gh-9776
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assert df.iloc[0:1, :].testattr == "XXX"
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# see gh-10553
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unpickled = tm.round_trip_pickle(df)
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tm.assert_frame_equal(df, unpickled)
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assert df._metadata == unpickled._metadata
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assert df.testattr == unpickled.testattr
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def test_indexing_sliced(self):
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# GH 11559
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df = tm.SubclassedDataFrame(
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{"X": [1, 2, 3], "Y": [4, 5, 6], "Z": [7, 8, 9]}, index=["a", "b", "c"]
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)
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res = df.loc[:, "X"]
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exp = tm.SubclassedSeries([1, 2, 3], index=list("abc"), name="X")
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tm.assert_series_equal(res, exp)
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assert isinstance(res, tm.SubclassedSeries)
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res = df.iloc[:, 1]
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exp = tm.SubclassedSeries([4, 5, 6], index=list("abc"), name="Y")
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tm.assert_series_equal(res, exp)
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assert isinstance(res, tm.SubclassedSeries)
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res = df.loc[:, "Z"]
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exp = tm.SubclassedSeries([7, 8, 9], index=list("abc"), name="Z")
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tm.assert_series_equal(res, exp)
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assert isinstance(res, tm.SubclassedSeries)
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res = df.loc["a", :]
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exp = tm.SubclassedSeries([1, 4, 7], index=list("XYZ"), name="a")
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tm.assert_series_equal(res, exp)
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assert isinstance(res, tm.SubclassedSeries)
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res = df.iloc[1, :]
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exp = tm.SubclassedSeries([2, 5, 8], index=list("XYZ"), name="b")
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tm.assert_series_equal(res, exp)
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assert isinstance(res, tm.SubclassedSeries)
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res = df.loc["c", :]
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exp = tm.SubclassedSeries([3, 6, 9], index=list("XYZ"), name="c")
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tm.assert_series_equal(res, exp)
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assert isinstance(res, tm.SubclassedSeries)
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def test_subclass_attr_err_propagation(self):
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# GH 11808
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class A(DataFrame):
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@property
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def bar(self):
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return self.i_dont_exist
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with pytest.raises(AttributeError, match=".*i_dont_exist.*"):
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A().bar
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def test_subclass_align(self):
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# GH 12983
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df1 = tm.SubclassedDataFrame(
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{"a": [1, 3, 5], "b": [1, 3, 5]}, index=list("ACE")
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)
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df2 = tm.SubclassedDataFrame(
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{"c": [1, 2, 4], "d": [1, 2, 4]}, index=list("ABD")
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)
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res1, res2 = df1.align(df2, axis=0)
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exp1 = tm.SubclassedDataFrame(
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{"a": [1, np.nan, 3, np.nan, 5], "b": [1, np.nan, 3, np.nan, 5]},
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index=list("ABCDE"),
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)
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exp2 = tm.SubclassedDataFrame(
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{"c": [1, 2, np.nan, 4, np.nan], "d": [1, 2, np.nan, 4, np.nan]},
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index=list("ABCDE"),
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)
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assert isinstance(res1, tm.SubclassedDataFrame)
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tm.assert_frame_equal(res1, exp1)
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assert isinstance(res2, tm.SubclassedDataFrame)
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tm.assert_frame_equal(res2, exp2)
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res1, res2 = df1.a.align(df2.c)
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assert isinstance(res1, tm.SubclassedSeries)
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tm.assert_series_equal(res1, exp1.a)
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assert isinstance(res2, tm.SubclassedSeries)
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tm.assert_series_equal(res2, exp2.c)
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def test_subclass_align_combinations(self):
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# GH 12983
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df = tm.SubclassedDataFrame({"a": [1, 3, 5], "b": [1, 3, 5]}, index=list("ACE"))
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s = tm.SubclassedSeries([1, 2, 4], index=list("ABD"), name="x")
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# frame + series
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res1, res2 = df.align(s, axis=0)
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exp1 = tm.SubclassedDataFrame(
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{"a": [1, np.nan, 3, np.nan, 5], "b": [1, np.nan, 3, np.nan, 5]},
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index=list("ABCDE"),
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)
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# name is lost when
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exp2 = tm.SubclassedSeries(
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[1, 2, np.nan, 4, np.nan], index=list("ABCDE"), name="x"
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)
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assert isinstance(res1, tm.SubclassedDataFrame)
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tm.assert_frame_equal(res1, exp1)
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assert isinstance(res2, tm.SubclassedSeries)
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tm.assert_series_equal(res2, exp2)
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# series + frame
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res1, res2 = s.align(df)
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assert isinstance(res1, tm.SubclassedSeries)
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tm.assert_series_equal(res1, exp2)
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assert isinstance(res2, tm.SubclassedDataFrame)
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tm.assert_frame_equal(res2, exp1)
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def test_subclass_iterrows(self):
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# GH 13977
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df = tm.SubclassedDataFrame({"a": [1]})
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for i, row in df.iterrows():
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assert isinstance(row, tm.SubclassedSeries)
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tm.assert_series_equal(row, df.loc[i])
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def test_subclass_stack(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
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index=["a", "b", "c"],
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columns=["X", "Y", "Z"],
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)
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res = df.stack()
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exp = tm.SubclassedSeries(
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[1, 2, 3, 4, 5, 6, 7, 8, 9], index=[list("aaabbbccc"), list("XYZXYZXYZ")]
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)
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tm.assert_series_equal(res, exp)
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def test_subclass_stack_multi(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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[[10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33], [40, 41, 42, 43]],
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index=MultiIndex.from_tuples(
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list(zip(list("AABB"), list("cdcd"))), names=["aaa", "ccc"]
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),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWXX"), list("yzyz"))), names=["www", "yyy"]
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),
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)
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exp = tm.SubclassedDataFrame(
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[
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[10, 12],
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[11, 13],
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[20, 22],
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[21, 23],
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[30, 32],
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[31, 33],
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[40, 42],
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[41, 43],
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],
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index=MultiIndex.from_tuples(
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list(zip(list("AAAABBBB"), list("ccddccdd"), list("yzyzyzyz"))),
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names=["aaa", "ccc", "yyy"],
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),
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columns=Index(["W", "X"], name="www"),
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)
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res = df.stack()
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tm.assert_frame_equal(res, exp)
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res = df.stack("yyy")
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tm.assert_frame_equal(res, exp)
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exp = tm.SubclassedDataFrame(
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[
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[10, 11],
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[12, 13],
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[20, 21],
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[22, 23],
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[30, 31],
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[32, 33],
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[40, 41],
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[42, 43],
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],
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index=MultiIndex.from_tuples(
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list(zip(list("AAAABBBB"), list("ccddccdd"), list("WXWXWXWX"))),
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names=["aaa", "ccc", "www"],
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),
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columns=Index(["y", "z"], name="yyy"),
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)
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res = df.stack("www")
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tm.assert_frame_equal(res, exp)
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def test_subclass_stack_multi_mixed(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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[
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[10, 11, 12.0, 13.0],
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[20, 21, 22.0, 23.0],
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[30, 31, 32.0, 33.0],
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[40, 41, 42.0, 43.0],
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],
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index=MultiIndex.from_tuples(
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list(zip(list("AABB"), list("cdcd"))), names=["aaa", "ccc"]
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),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWXX"), list("yzyz"))), names=["www", "yyy"]
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),
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)
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exp = tm.SubclassedDataFrame(
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[
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[10, 12.0],
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[11, 13.0],
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[20, 22.0],
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[21, 23.0],
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[30, 32.0],
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[31, 33.0],
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[40, 42.0],
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[41, 43.0],
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],
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index=MultiIndex.from_tuples(
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list(zip(list("AAAABBBB"), list("ccddccdd"), list("yzyzyzyz"))),
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names=["aaa", "ccc", "yyy"],
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),
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columns=Index(["W", "X"], name="www"),
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)
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res = df.stack()
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tm.assert_frame_equal(res, exp)
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res = df.stack("yyy")
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tm.assert_frame_equal(res, exp)
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exp = tm.SubclassedDataFrame(
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[
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[10.0, 11.0],
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[12.0, 13.0],
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[20.0, 21.0],
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[22.0, 23.0],
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[30.0, 31.0],
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[32.0, 33.0],
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[40.0, 41.0],
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[42.0, 43.0],
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],
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index=MultiIndex.from_tuples(
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list(zip(list("AAAABBBB"), list("ccddccdd"), list("WXWXWXWX"))),
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names=["aaa", "ccc", "www"],
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),
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columns=Index(["y", "z"], name="yyy"),
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)
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res = df.stack("www")
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tm.assert_frame_equal(res, exp)
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def test_subclass_unstack(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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[[1, 2, 3], [4, 5, 6], [7, 8, 9]],
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index=["a", "b", "c"],
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columns=["X", "Y", "Z"],
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)
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res = df.unstack()
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exp = tm.SubclassedSeries(
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[1, 4, 7, 2, 5, 8, 3, 6, 9], index=[list("XXXYYYZZZ"), list("abcabcabc")]
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)
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tm.assert_series_equal(res, exp)
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def test_subclass_unstack_multi(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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[[10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33], [40, 41, 42, 43]],
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index=MultiIndex.from_tuples(
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list(zip(list("AABB"), list("cdcd"))), names=["aaa", "ccc"]
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),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWXX"), list("yzyz"))), names=["www", "yyy"]
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),
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)
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exp = tm.SubclassedDataFrame(
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[[10, 20, 11, 21, 12, 22, 13, 23], [30, 40, 31, 41, 32, 42, 33, 43]],
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index=Index(["A", "B"], name="aaa"),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWWWXXXX"), list("yyzzyyzz"), list("cdcdcdcd"))),
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names=["www", "yyy", "ccc"],
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),
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)
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res = df.unstack()
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tm.assert_frame_equal(res, exp)
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res = df.unstack("ccc")
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tm.assert_frame_equal(res, exp)
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exp = tm.SubclassedDataFrame(
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[[10, 30, 11, 31, 12, 32, 13, 33], [20, 40, 21, 41, 22, 42, 23, 43]],
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index=Index(["c", "d"], name="ccc"),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWWWXXXX"), list("yyzzyyzz"), list("ABABABAB"))),
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names=["www", "yyy", "aaa"],
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),
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)
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res = df.unstack("aaa")
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tm.assert_frame_equal(res, exp)
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def test_subclass_unstack_multi_mixed(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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[
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[10, 11, 12.0, 13.0],
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[20, 21, 22.0, 23.0],
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[30, 31, 32.0, 33.0],
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[40, 41, 42.0, 43.0],
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],
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index=MultiIndex.from_tuples(
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list(zip(list("AABB"), list("cdcd"))), names=["aaa", "ccc"]
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),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWXX"), list("yzyz"))), names=["www", "yyy"]
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),
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)
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exp = tm.SubclassedDataFrame(
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[
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[10, 20, 11, 21, 12.0, 22.0, 13.0, 23.0],
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[30, 40, 31, 41, 32.0, 42.0, 33.0, 43.0],
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],
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index=Index(["A", "B"], name="aaa"),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWWWXXXX"), list("yyzzyyzz"), list("cdcdcdcd"))),
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names=["www", "yyy", "ccc"],
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),
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)
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res = df.unstack()
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tm.assert_frame_equal(res, exp)
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res = df.unstack("ccc")
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tm.assert_frame_equal(res, exp)
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exp = tm.SubclassedDataFrame(
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[
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[10, 30, 11, 31, 12.0, 32.0, 13.0, 33.0],
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[20, 40, 21, 41, 22.0, 42.0, 23.0, 43.0],
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],
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index=Index(["c", "d"], name="ccc"),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWWWXXXX"), list("yyzzyyzz"), list("ABABABAB"))),
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names=["www", "yyy", "aaa"],
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),
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)
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res = df.unstack("aaa")
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tm.assert_frame_equal(res, exp)
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def test_subclass_pivot(self):
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# GH 15564
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df = tm.SubclassedDataFrame(
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{
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"index": ["A", "B", "C", "C", "B", "A"],
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"columns": ["One", "One", "One", "Two", "Two", "Two"],
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"values": [1.0, 2.0, 3.0, 3.0, 2.0, 1.0],
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}
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)
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pivoted = df.pivot(index="index", columns="columns", values="values")
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expected = tm.SubclassedDataFrame(
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{
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"One": {"A": 1.0, "B": 2.0, "C": 3.0},
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"Two": {"A": 1.0, "B": 2.0, "C": 3.0},
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}
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)
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expected.index.name, expected.columns.name = "index", "columns"
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tm.assert_frame_equal(pivoted, expected)
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def test_subclassed_melt(self):
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# GH 15564
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cheese = tm.SubclassedDataFrame(
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{
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"first": ["John", "Mary"],
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"last": ["Doe", "Bo"],
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"height": [5.5, 6.0],
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"weight": [130, 150],
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}
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)
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melted = pd.melt(cheese, id_vars=["first", "last"])
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expected = tm.SubclassedDataFrame(
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[
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["John", "Doe", "height", 5.5],
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["Mary", "Bo", "height", 6.0],
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["John", "Doe", "weight", 130],
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["Mary", "Bo", "weight", 150],
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],
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columns=["first", "last", "variable", "value"],
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)
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tm.assert_frame_equal(melted, expected)
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def test_subclassed_wide_to_long(self):
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# GH 9762
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np.random.seed(123)
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x = np.random.randn(3)
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df = tm.SubclassedDataFrame(
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{
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"A1970": {0: "a", 1: "b", 2: "c"},
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"A1980": {0: "d", 1: "e", 2: "f"},
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"B1970": {0: 2.5, 1: 1.2, 2: 0.7},
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"B1980": {0: 3.2, 1: 1.3, 2: 0.1},
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"X": dict(zip(range(3), x)),
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}
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)
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df["id"] = df.index
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exp_data = {
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"X": x.tolist() + x.tolist(),
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"A": ["a", "b", "c", "d", "e", "f"],
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"B": [2.5, 1.2, 0.7, 3.2, 1.3, 0.1],
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"year": [1970, 1970, 1970, 1980, 1980, 1980],
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"id": [0, 1, 2, 0, 1, 2],
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}
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expected = tm.SubclassedDataFrame(exp_data)
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expected = expected.set_index(["id", "year"])[["X", "A", "B"]]
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long_frame = pd.wide_to_long(df, ["A", "B"], i="id", j="year")
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tm.assert_frame_equal(long_frame, expected)
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def test_subclassed_apply(self):
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# GH 19822
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def check_row_subclass(row):
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assert isinstance(row, tm.SubclassedSeries)
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def strech(row):
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if row["variable"] == "height":
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row["value"] += 0.5
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return row
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df = tm.SubclassedDataFrame(
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[
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["John", "Doe", "height", 5.5],
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["Mary", "Bo", "height", 6.0],
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["John", "Doe", "weight", 130],
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["Mary", "Bo", "weight", 150],
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],
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columns=["first", "last", "variable", "value"],
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)
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df.apply(lambda x: check_row_subclass(x))
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df.apply(lambda x: check_row_subclass(x), axis=1)
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expected = tm.SubclassedDataFrame(
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[
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["John", "Doe", "height", 6.0],
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["Mary", "Bo", "height", 6.5],
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["John", "Doe", "weight", 130],
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["Mary", "Bo", "weight", 150],
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],
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columns=["first", "last", "variable", "value"],
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)
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result = df.apply(lambda x: strech(x), axis=1)
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assert isinstance(result, tm.SubclassedDataFrame)
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tm.assert_frame_equal(result, expected)
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expected = tm.SubclassedDataFrame([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]])
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result = df.apply(lambda x: tm.SubclassedSeries([1, 2, 3]), axis=1)
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assert isinstance(result, tm.SubclassedDataFrame)
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tm.assert_frame_equal(result, expected)
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result = df.apply(lambda x: [1, 2, 3], axis=1, result_type="expand")
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assert isinstance(result, tm.SubclassedDataFrame)
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tm.assert_frame_equal(result, expected)
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expected = tm.SubclassedSeries([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]])
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result = df.apply(lambda x: [1, 2, 3], axis=1)
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assert not isinstance(result, tm.SubclassedDataFrame)
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tm.assert_series_equal(result, expected)
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def test_subclassed_reductions(self, all_reductions):
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# GH 25596
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df = tm.SubclassedDataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
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result = getattr(df, all_reductions)()
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assert isinstance(result, tm.SubclassedSeries)
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def test_subclassed_count(self):
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df = tm.SubclassedDataFrame(
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{
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"Person": ["John", "Myla", "Lewis", "John", "Myla"],
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"Age": [24.0, np.nan, 21.0, 33, 26],
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"Single": [False, True, True, True, False],
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}
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)
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result = df.count()
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assert isinstance(result, tm.SubclassedSeries)
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df = tm.SubclassedDataFrame({"A": [1, 0, 3], "B": [0, 5, 6], "C": [7, 8, 0]})
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result = df.count()
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assert isinstance(result, tm.SubclassedSeries)
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df = tm.SubclassedDataFrame(
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[[10, 11, 12, 13], [20, 21, 22, 23], [30, 31, 32, 33], [40, 41, 42, 43]],
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index=MultiIndex.from_tuples(
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list(zip(list("AABB"), list("cdcd"))), names=["aaa", "ccc"]
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),
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columns=MultiIndex.from_tuples(
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list(zip(list("WWXX"), list("yzyz"))), names=["www", "yyy"]
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),
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)
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result = df.count(level=1)
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assert isinstance(result, tm.SubclassedDataFrame)
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df = tm.SubclassedDataFrame()
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result = df.count()
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assert isinstance(result, tm.SubclassedSeries)
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def test_isin(self):
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df = tm.SubclassedDataFrame(
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{"num_legs": [2, 4], "num_wings": [2, 0]}, index=["falcon", "dog"]
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)
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result = df.isin([0, 2])
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assert isinstance(result, tm.SubclassedDataFrame)
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def test_duplicated(self):
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df = tm.SubclassedDataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
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result = df.duplicated()
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assert isinstance(result, tm.SubclassedSeries)
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df = tm.SubclassedDataFrame()
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result = df.duplicated()
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assert isinstance(result, tm.SubclassedSeries)
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@pytest.mark.parametrize("idx_method", ["idxmax", "idxmin"])
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def test_idx(self, idx_method):
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df = tm.SubclassedDataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
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result = getattr(df, idx_method)()
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assert isinstance(result, tm.SubclassedSeries)
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def test_dot(self):
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df = tm.SubclassedDataFrame([[0, 1, -2, -1], [1, 1, 1, 1]])
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s = tm.SubclassedSeries([1, 1, 2, 1])
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result = df.dot(s)
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assert isinstance(result, tm.SubclassedSeries)
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df = tm.SubclassedDataFrame([[0, 1, -2, -1], [1, 1, 1, 1]])
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s = tm.SubclassedDataFrame([1, 1, 2, 1])
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result = df.dot(s)
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assert isinstance(result, tm.SubclassedDataFrame)
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def test_memory_usage(self):
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df = tm.SubclassedDataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
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result = df.memory_usage()
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assert isinstance(result, tm.SubclassedSeries)
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result = df.memory_usage(index=False)
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assert isinstance(result, tm.SubclassedSeries)
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@td.skip_if_no_scipy
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def test_corrwith(self):
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index = ["a", "b", "c", "d", "e"]
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columns = ["one", "two", "three", "four"]
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df1 = tm.SubclassedDataFrame(
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np.random.randn(5, 4), index=index, columns=columns
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)
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df2 = tm.SubclassedDataFrame(
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np.random.randn(4, 4), index=index[:4], columns=columns
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)
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correls = df1.corrwith(df2, axis=1, drop=True, method="kendall")
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assert isinstance(correls, (tm.SubclassedSeries))
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def test_asof(self):
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N = 3
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rng = pd.date_range("1/1/1990", periods=N, freq="53s")
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df = tm.SubclassedDataFrame(
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{
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"A": [np.nan, np.nan, np.nan],
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"B": [np.nan, np.nan, np.nan],
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"C": [np.nan, np.nan, np.nan],
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},
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index=rng,
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)
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result = df.asof(rng[-2:])
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assert isinstance(result, tm.SubclassedDataFrame)
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result = df.asof(rng[-2])
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assert isinstance(result, tm.SubclassedSeries)
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result = df.asof("1989-12-31")
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assert isinstance(result, tm.SubclassedSeries)
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def test_idxmin_preserves_subclass(self):
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# GH 28330
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df = tm.SubclassedDataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
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result = df.idxmin()
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assert isinstance(result, tm.SubclassedSeries)
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def test_idxmax_preserves_subclass(self):
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# GH 28330
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df = tm.SubclassedDataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
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result = df.idxmax()
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assert isinstance(result, tm.SubclassedSeries)
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def test_equals_subclass(self):
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# https://github.com/pandas-dev/pandas/pull/34402
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# allow subclass in both directions
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df1 = pd.DataFrame({"a": [1, 2, 3]})
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df2 = tm.SubclassedDataFrame({"a": [1, 2, 3]})
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assert df1.equals(df2)
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assert df2.equals(df1)
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