def test_get_dummies_kwargs(self): # pser = pd.Series([1, 1, 1, 2, 2, 1, 3, 4], dtype='category') pser = pd.Series([1, 1, 1, 2, 2, 1, 3, 4]) psser = ps.from_pandas(pser) self.assert_eq( ps.get_dummies(psser, prefix="X", prefix_sep="-"), pd.get_dummies(pser, prefix="X", prefix_sep="-", dtype=np.int8), ) self.assert_eq( ps.get_dummies(psser, drop_first=True), pd.get_dummies(pser, drop_first=True, dtype=np.int8), ) # nan # pser = pd.Series([1, 1, 1, 2, np.nan, 3, np.nan, 5], dtype='category') pser = pd.Series([1, 1, 1, 2, np.nan, 3, np.nan, 5]) psser = ps.from_pandas(pser) self.assert_eq(ps.get_dummies(psser), pd.get_dummies(pser, dtype=np.int8), almost=True) # dummy_na self.assert_eq(ps.get_dummies(psser, dummy_na=True), pd.get_dummies(pser, dummy_na=True, dtype=np.int8))
def test_get_dummies(self): for pdf_or_ps in [ pd.Series([1, 1, 1, 2, 2, 1, 3, 4]), # pd.Series([1, 1, 1, 2, 2, 1, 3, 4], dtype='category'), # pd.Series(pd.Categorical([1, 1, 1, 2, 2, 1, 3, 4], # categories=[4, 3, 2, 1])), pd.DataFrame({ "a": [1, 2, 3, 4, 4, 3, 2, 1], # 'b': pd.Categorical(list('abcdabcd')), "b": list("abcdabcd"), }), pd.DataFrame({ 10: [1, 2, 3, 4, 4, 3, 2, 1], 20: list("abcdabcd") }), ]: psdf_or_psser = ps.from_pandas(pdf_or_ps) self.assert_eq(ps.get_dummies(psdf_or_psser), pd.get_dummies(pdf_or_ps, dtype=np.int8)) psser = ps.Series([1, 1, 1, 2, 2, 1, 3, 4]) with self.assertRaisesRegex( NotImplementedError, "get_dummies currently does not support sparse"): ps.get_dummies(psser, sparse=True)
def test_get_dummies_boolean(self): pdf = pd.DataFrame({"b": [True, False, True]}) psdf = ps.from_pandas(pdf) self.assert_eq(ps.get_dummies(psdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(psdf.b), pd.get_dummies(pdf.b, dtype=np.int8))
def test_get_dummies_decimal(self): pdf = pd.DataFrame({"d": [Decimal(1.0), Decimal(2.0), Decimal(1)]}) psdf = ps.from_pandas(pdf) self.assert_eq(ps.get_dummies(psdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(psdf.d), pd.get_dummies(pdf.d, dtype=np.int8), almost=True)
def test_get_dummies_boolean(self): pdf = pd.DataFrame({"b": [True, False, True]}) kdf = ps.from_pandas(pdf) if LooseVersion(pyspark.__version__) >= LooseVersion("2.4"): self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.b), pd.get_dummies(pdf.b, dtype=np.int8)) else: with self.sql_conf({SPARK_CONF_ARROW_ENABLED: False}): self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.b), pd.get_dummies(pdf.b, dtype=np.int8))
def test_get_dummies_decimal(self): pdf = pd.DataFrame({"d": [Decimal(1.0), Decimal(2.0), Decimal(1)]}) kdf = ps.from_pandas(pdf) if LooseVersion(pyspark.__version__) >= LooseVersion("2.4"): self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.d), pd.get_dummies(pdf.d, dtype=np.int8), almost=True) else: with self.sql_conf({SPARK_CONF_ARROW_ENABLED: False}): self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.d), pd.get_dummies(pdf.d, dtype=np.int8), almost=True)
def test_get_dummies_date_datetime(self): pdf = pd.DataFrame( { "d": [ datetime.date(2019, 1, 1), datetime.date(2019, 1, 2), datetime.date(2019, 1, 1), ], "dt": [ datetime.datetime(2019, 1, 1, 0, 0, 0), datetime.datetime(2019, 1, 1, 0, 0, 1), datetime.datetime(2019, 1, 1, 0, 0, 0), ], } ) kdf = ps.from_pandas(pdf) self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.d), pd.get_dummies(pdf.d, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.dt), pd.get_dummies(pdf.dt, dtype=np.int8))
def test_get_dummies_date_datetime(self): pdf = pd.DataFrame({ "d": [ datetime.date(2019, 1, 1), datetime.date(2019, 1, 2), datetime.date(2019, 1, 1), ], "dt": [ datetime.datetime(2019, 1, 1, 0, 0, 0), datetime.datetime(2019, 1, 1, 0, 0, 1), datetime.datetime(2019, 1, 1, 0, 0, 0), ], }) kdf = ps.from_pandas(pdf) if LooseVersion(pyspark.__version__) >= LooseVersion("2.4"): self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.d), pd.get_dummies(pdf.d, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.dt), pd.get_dummies(pdf.dt, dtype=np.int8)) else: with self.sql_conf({SPARK_CONF_ARROW_ENABLED: False}): self.assert_eq(ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.d), pd.get_dummies(pdf.d, dtype=np.int8)) self.assert_eq(ps.get_dummies(kdf.dt), pd.get_dummies(pdf.dt, dtype=np.int8))
def test_get_dummies_dtype(self): pdf = pd.DataFrame( { # "A": pd.Categorical(['a', 'b', 'a'], categories=['a', 'b', 'c']), "A": ["a", "b", "a"], "B": [0, 0, 1], } ) psdf = ps.from_pandas(pdf) exp = pd.get_dummies(pdf) exp = exp.astype({"A_a": "float64", "A_b": "float64"}) res = ps.get_dummies(psdf, dtype="float64") self.assert_eq(res, exp)
def test_get_dummies_dtype(self): pdf = pd.DataFrame({ # "A": pd.Categorical(['a', 'b', 'a'], categories=['a', 'b', 'c']), "A": ["a", "b", "a"], "B": [0, 0, 1], }) kdf = ps.from_pandas(pdf) if LooseVersion("0.23.0") <= LooseVersion(pd.__version__): exp = pd.get_dummies(pdf, dtype="float64") else: exp = pd.get_dummies(pdf) exp = exp.astype({"A_a": "float64", "A_b": "float64"}) res = ps.get_dummies(kdf, dtype="float64") self.assert_eq(res, exp)
def test_get_dummies_object(self): pdf = pd.DataFrame({ "a": [1, 2, 3, 4, 4, 3, 2, 1], # 'a': pd.Categorical([1, 2, 3, 4, 4, 3, 2, 1]), "b": list("abcdabcd"), # 'c': pd.Categorical(list('abcdabcd')), "c": list("abcdabcd"), }) psdf = ps.from_pandas(pdf) # Explicitly exclude object columns self.assert_eq( ps.get_dummies(psdf, columns=["a", "c"]), pd.get_dummies(pdf, columns=["a", "c"], dtype=np.int8), ) self.assert_eq(ps.get_dummies(psdf), pd.get_dummies(pdf, dtype=np.int8)) self.assert_eq(ps.get_dummies(psdf.b), pd.get_dummies(pdf.b, dtype=np.int8)) self.assert_eq(ps.get_dummies(psdf, columns=["b"]), pd.get_dummies(pdf, columns=["b"], dtype=np.int8)) self.assertRaises(KeyError, lambda: ps.get_dummies(psdf, columns=("a", "c"))) self.assertRaises(TypeError, lambda: ps.get_dummies(psdf, columns="b")) # non-string names pdf = pd.DataFrame({ 10: [1, 2, 3, 4, 4, 3, 2, 1], 20: list("abcdabcd"), 30: list("abcdabcd") }) psdf = ps.from_pandas(pdf) self.assert_eq( ps.get_dummies(psdf, columns=[10, 30]), pd.get_dummies(pdf, columns=[10, 30], dtype=np.int8), ) self.assertRaises(TypeError, lambda: ps.get_dummies(psdf, columns=10))
def test_get_dummies_multiindex_columns(self): pdf = pd.DataFrame( { ("x", "a", "1"): [1, 2, 3, 4, 4, 3, 2, 1], ("x", "b", "2"): list("abcdabcd"), ("y", "c", "3"): list("abcdabcd"), } ) kdf = ps.from_pandas(pdf) self.assert_eq( ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8).rename(columns=name_like_string) ) self.assert_eq( ps.get_dummies(kdf, columns=[("y", "c", "3"), ("x", "a", "1")]), pd.get_dummies(pdf, columns=[("y", "c", "3"), ("x", "a", "1")], dtype=np.int8).rename( columns=name_like_string ), ) self.assert_eq( ps.get_dummies(kdf, columns=["x"]), pd.get_dummies(pdf, columns=["x"], dtype=np.int8).rename(columns=name_like_string), ) self.assert_eq( ps.get_dummies(kdf, columns=("x", "a")), pd.get_dummies(pdf, columns=("x", "a"), dtype=np.int8).rename(columns=name_like_string), ) self.assertRaises(KeyError, lambda: ps.get_dummies(kdf, columns=["z"])) self.assertRaises(KeyError, lambda: ps.get_dummies(kdf, columns=("x", "c"))) self.assertRaises(ValueError, lambda: ps.get_dummies(kdf, columns=[("x",), "c"])) self.assertRaises(TypeError, lambda: ps.get_dummies(kdf, columns="x")) # non-string names pdf = pd.DataFrame( { ("x", 1, "a"): [1, 2, 3, 4, 4, 3, 2, 1], ("x", 2, "b"): list("abcdabcd"), ("y", 3, "c"): list("abcdabcd"), } ) kdf = ps.from_pandas(pdf) self.assert_eq( ps.get_dummies(kdf), pd.get_dummies(pdf, dtype=np.int8).rename(columns=name_like_string) ) self.assert_eq( ps.get_dummies(kdf, columns=[("y", 3, "c"), ("x", 1, "a")]), pd.get_dummies(pdf, columns=[("y", 3, "c"), ("x", 1, "a")], dtype=np.int8).rename( columns=name_like_string ), ) self.assert_eq( ps.get_dummies(kdf, columns=["x"]), pd.get_dummies(pdf, columns=["x"], dtype=np.int8).rename(columns=name_like_string), ) self.assert_eq( ps.get_dummies(kdf, columns=("x", 1)), pd.get_dummies(pdf, columns=("x", 1), dtype=np.int8).rename(columns=name_like_string), )
def test_get_dummies_prefix(self): pdf = pd.DataFrame({"A": ["a", "b", "a"], "B": ["b", "a", "c"], "D": [0, 0, 1]}) kdf = ps.from_pandas(pdf) self.assert_eq( ps.get_dummies(kdf, prefix=["foo", "bar"]), pd.get_dummies(pdf, prefix=["foo", "bar"], dtype=np.int8), ) self.assert_eq( ps.get_dummies(kdf, prefix=["foo"], columns=["B"]), pd.get_dummies(pdf, prefix=["foo"], columns=["B"], dtype=np.int8), ) self.assert_eq( ps.get_dummies(kdf, prefix={"A": "foo", "B": "bar"}), pd.get_dummies(pdf, prefix={"A": "foo", "B": "bar"}, dtype=np.int8), ) self.assert_eq( ps.get_dummies(kdf, prefix={"B": "foo", "A": "bar"}), pd.get_dummies(pdf, prefix={"B": "foo", "A": "bar"}, dtype=np.int8), ) self.assert_eq( ps.get_dummies(kdf, prefix={"A": "foo", "B": "bar"}, columns=["A", "B"]), pd.get_dummies(pdf, prefix={"A": "foo", "B": "bar"}, columns=["A", "B"], dtype=np.int8), ) with self.assertRaisesRegex(NotImplementedError, "string types"): ps.get_dummies(kdf, prefix="foo") with self.assertRaisesRegex(ValueError, "Length of 'prefix' \\(1\\) .* \\(2\\)"): ps.get_dummies(kdf, prefix=["foo"]) with self.assertRaisesRegex(ValueError, "Length of 'prefix' \\(2\\) .* \\(1\\)"): ps.get_dummies(kdf, prefix=["foo", "bar"], columns=["B"]) pser = pd.Series([1, 1, 1, 2, 2, 1, 3, 4], name="A") kser = ps.from_pandas(pser) self.assert_eq( ps.get_dummies(kser, prefix="foo"), pd.get_dummies(pser, prefix="foo", dtype=np.int8) ) # columns are ignored. self.assert_eq( ps.get_dummies(kser, prefix=["foo"], columns=["B"]), pd.get_dummies(pser, prefix=["foo"], columns=["B"], dtype=np.int8), )