def test_series_replace_with_nulls():
a1 = np.array([0, 1, 2, 3, 4])
# Numerical
a2 = np.array([-10, 1, 2, 3, 4])
sr1 = Series(a1)
sr2 = sr1.replace(0, None).fillna(-10)
np.testing.assert_equal(sr2.to_array(), a2)
# List input
a6 = np.array([-10, 6, 2, 3, 4])
sr6 = sr1.replace([0, 1], [None, 6]).fillna(-10)
np.testing.assert_equal(sr6.to_array(), a6)
a7 = np.array([5.5, 6.5, 2, 3, 4, -10])
sr1 = Series([0, 1, 2, 3, 4, None])
sr7 = sr1.replace([0, 1], [5.5, 6.5]).fillna(-10)
np.testing.assert_equal(sr7.to_array(), a7)
# Series input
a8 = np.array([-10, -10, -10, 3, 4, -10])
sr8 = sr1.replace(sr1[:3], None).fillna(-10)
np.testing.assert_equal(sr8.to_array(), a8)
a9 = np.array([-10, 6.5, 2, 3, 4, -10])
sr9 = sr1.replace([0, 1], [None, 6.5]).fillna(-10)
np.testing.assert_equal(sr9.to_array(), a9)
def test_series_replace():
a1 = np.array([0, 1, 2, 3, 4])
# Numerical
a2 = np.array([5, 1, 2, 3, 4])
sr1 = Series(a1)
sr2 = sr1.replace(0, 5)
assert_eq(a2, sr2.to_array())
# Categorical
psr3 = pd.Series(["one", "two", "three"], dtype="category")
psr4 = psr3.replace("one", "two")
sr3 = Series.from_pandas(psr3)
sr4 = sr3.replace("one", "two")
assert_eq(psr4, sr4)
psr5 = psr3.replace("one", "five")
sr5 = sr3.replace("one", "five")
assert_eq(psr5, sr5)
# List input
a6 = np.array([5, 6, 2, 3, 4])
sr6 = sr1.replace([0, 1], [5, 6])
assert_eq(a6, sr6.to_array())
with pytest.raises(TypeError):
sr1.replace([0, 1], [5.5, 6.5])
# Series input
a8 = np.array([5, 5, 5, 3, 4])
sr8 = sr1.replace(sr1[:3].to_array(), 5)
assert_eq(a8, sr8.to_array())
# large input containing null
sr9 = Series(list(range(400)) + [None])
sr10 = sr9.replace([22, 323, 27, 0], None)
assert sr10.null_count == 5
assert len(sr10.to_array()) == (401 - 5)
sr11 = sr9.replace([22, 323, 27, 0], -1)
assert sr11.null_count == 1
assert len(sr11.to_array()) == (401 - 1)
# large input not containing nulls
sr9 = sr9.fillna(-11)
sr12 = sr9.replace([22, 323, 27, 0], None)
assert sr12.null_count == 4
assert len(sr12.to_array()) == (401 - 4)
sr13 = sr9.replace([22, 323, 27, 0], -1)
assert sr13.null_count == 0
assert len(sr13.to_array()) == 401
def test_series_replace_with_nulls():
a1 = np.array([0, 1, 2, 3, 4])
# Numerical
a2 = np.array([-10, 1, 2, 3, 4])
sr1 = Series(a1)
sr2 = sr1.replace(0, None).fillna(-10)
assert_eq(a2, sr2.to_array())
# List input
a6 = np.array([-10, 6, 2, 3, 4])
sr6 = sr1.replace([0, 1], [None, 6]).fillna(-10)
assert_eq(a6, sr6.to_array())
sr1 = Series([0, 1, 2, 3, 4, None])
with pytest.raises(TypeError):
sr1.replace([0, 1], [5.5, 6.5]).fillna(-10)
# Series input
a8 = np.array([-10, -10, -10, 3, 4, -10])
sr8 = sr1.replace(cudf.Series([-10] * 3, index=sr1[:3]), None).fillna(-10)
assert_eq(a8, sr8.to_array())
a9 = np.array([-10, 6, 2, 3, 4, -10])
sr9 = sr1.replace([0, 1], [None, 6]).fillna(-10)
assert_eq(a9, sr9.to_array())
def test_series_replace():
a1 = np.array([0, 1, 2, 3, 4])
# Numerical
a2 = np.array([5, 1, 2, 3, 4])
sr1 = Series(a1)
sr2 = sr1.replace(0, 5)
np.testing.assert_equal(sr2.to_array(), a2)
# Categorical
psr3 = pd.Series(["one", "two", "three"], dtype="category")
psr4 = psr3.replace("one", "two")
sr3 = Series.from_pandas(psr3)
sr4 = sr3.replace("one", "two")
pd.testing.assert_series_equal(sr4.to_pandas(), psr4)
# List input
a6 = np.array([5, 6, 2, 3, 4])
sr6 = sr1.replace([0, 1], [5, 6])
np.testing.assert_equal(sr6.to_array(), a6)
a7 = np.array([5.5, 6.5, 2, 3, 4])
sr7 = sr1.replace([0, 1], [5.5, 6.5])
np.testing.assert_equal(sr7.to_array(), a7)
# Series input
a8 = np.array([5, 5, 5, 3, 4])
sr8 = sr1.replace(sr1[:3], 5)
np.testing.assert_equal(sr8.to_array(), a8)
# large input containing null
sr9 = Series(list(range(400)) + [None])
sr10 = sr9.replace([22, 323, 27, 0], None)
assert sr10.null_count == 5
assert len(sr10.to_array()) == (401 - 5)
sr11 = sr9.replace([22, 323, 27, 0], -1)
assert sr11.null_count == 1
assert len(sr11.to_array()) == (401 - 1)
# large input not containing nulls
sr9 = sr9.fillna(-11)
sr12 = sr9.replace([22, 323, 27, 0], None)
assert sr12.null_count == 4
assert len(sr12.to_array()) == (401 - 4)
sr13 = sr9.replace([22, 323, 27, 0], -1)
assert sr13.null_count == 0
assert len(sr13.to_array()) == 401
def test_series_multiple_times_with_nulls():
sr = Series([1, 2, 3, None])
expected = Series([None, None, None, None], dtype=np.int64)
for i in range(3):
got = sr.replace([1, 2, 3], None)
assert_eq(expected, got)
# BUG: #2695
# The following series will acquire a chunk of memory and update with
# values, but these values may still linger even after the memory
# gets released. This memory space might get used for replace in
# subsequent calls and the memory used for mask may have junk values.
# So, if it is not updated properly, the result would be wrong.
# So, this will help verify that scenario.
Series([1, 1, 1, None])
def test_replace_inplace():
data = np.array([5, 1, 2, 3, 4])
sr = Series(data)
psr = pd.Series(data)
sr_copy = sr.copy()
psr_copy = psr.copy()
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr.replace(5, 0, inplace=True)
psr.replace(5, 0, inplace=True)
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr = Series(data)
psr = pd.Series(data)
sr_copy = sr.copy()
psr_copy = psr.copy()
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr.replace({5: 0, 3: -5})
psr.replace({5: 0, 3: -5})
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
srr = sr.replace()
psrr = psr.replace()
assert_eq(srr, psrr)
psr = pd.Series(["one", "two", "three"], dtype="category")
sr = Series.from_pandas(psr)
sr_copy = sr.copy()
psr_copy = psr.copy()
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr.replace("one", "two", inplace=True)
psr.replace("one", "two", inplace=True)
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
pdf = pd.DataFrame({"A": [0, 1, 2, 3, 4], "B": [5, 6, 7, 8, 9]})
gdf = DataFrame.from_pandas(pdf)
pdf_copy = pdf.copy()
gdf_copy = gdf.copy()
assert_eq(pdf, gdf)
assert_eq(pdf_copy, gdf_copy)
pdf.replace(5, 0, inplace=True)
gdf.replace(5, 0, inplace=True)
assert_eq(pdf, gdf)
assert_eq(pdf_copy, gdf_copy)
pds = pd.Series([1, 2, 3, 45])
gds = Series.from_pandas(pds)
vals = np.array([]).astype(int)
assert_eq(pds.replace(vals, -1), gds.replace(vals, -1))
pds.replace(vals, 77, inplace=True)
gds.replace(vals, 77, inplace=True)
assert_eq(pds, gds)
pdf = pd.DataFrame({"a": [1, 2, 3, 4, 5, 666]})
gdf = DataFrame.from_pandas(pdf)
assert_eq(pdf.replace({"a": 2}, {"a": -33}),
gdf.replace({"a": 2}, {"a": -33}))
assert_eq(
pdf.replace({"a": [2, 5]}, {"a": [9, 10]}),
gdf.replace({"a": [2, 5]}, {"a": [9, 10]}),
)
assert_eq(
pdf.replace([], []),
gdf.replace([], []),
)
with pytest.raises(TypeError):
pdf.replace(-1, [])
with pytest.raises(TypeError):
gdf.replace(-1, [])
def test_replace_strings():
pdf = pd.Series(["a", "b", "c", "d"])
gdf = Series(["a", "b", "c", "d"])
assert_eq(pdf.replace("a", "e"), gdf.replace("a", "e"))
def test_replace_inplace():
data = np.array([5, 1, 2, 3, 4])
sr = Series(data)
psr = pd.Series(data)
sr_copy = sr.copy()
psr_copy = psr.copy()
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr.replace(5, 0, inplace=True)
psr.replace(5, 0, inplace=True)
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr = Series(data)
psr = pd.Series(data)
sr_copy = sr.copy()
psr_copy = psr.copy()
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr.replace({5: 0, 3: -5})
psr.replace({5: 0, 3: -5})
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
srr = sr.replace()
psrr = psr.replace()
assert_eq(srr, psrr)
psr = pd.Series(["one", "two", "three"], dtype="category")
sr = Series.from_pandas(psr)
sr_copy = sr.copy()
psr_copy = psr.copy()
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
sr.replace("one", "two", inplace=True)
psr.replace("one", "two", inplace=True)
assert_eq(sr, psr)
assert_eq(sr_copy, psr_copy)
pdf = pd.DataFrame({"A": [0, 1, 2, 3, 4], "B": [5, 6, 7, 8, 9]})
gdf = DataFrame.from_pandas(pdf)
pdf_copy = pdf.copy()
gdf_copy = gdf.copy()
assert_eq(pdf, gdf)
assert_eq(pdf_copy, gdf_copy)
pdf.replace(5, 0, inplace=True)
gdf.replace(5, 0, inplace=True)
assert_eq(pdf, gdf)
assert_eq(pdf_copy, gdf_copy)
pds = pd.Series([1, 2, 3, 45])
gds = Series.from_pandas(pds)
vals = np.array([]).astype(int)
assert_eq(pds.replace(vals, -1), gds.replace(vals, -1))
pds.replace(vals, 77, inplace=True)
gds.replace(vals, 77, inplace=True)
assert_eq(pds, gds)
pdf = pd.DataFrame({"a": [1, 2, 3, 4, 5, 666]})
gdf = DataFrame.from_pandas(pdf)
assert_eq(pdf.replace({"a": 2}, {"a": -33}),
gdf.replace({"a": 2}, {"a": -33}))
assert_eq(
pdf.replace({"a": [2, 5]}, {"a": [9, 10]}),
gdf.replace({"a": [2, 5]}, {"a": [9, 10]}),
)
assert_eq(
pdf.replace([], []),
gdf.replace([], []),
)
assert_exceptions_equal(
lfunc=pdf.replace,
rfunc=gdf.replace,
lfunc_args_and_kwargs=([], {
"to_replace": -1,
"value": []
}),
rfunc_args_and_kwargs=([], {
"to_replace": -1,
"value": []
}),
compare_error_message=False,
)
