394 lines
13 KiB
Python
394 lines
13 KiB
Python
import pytest
|
|
|
|
import pandas as pd
|
|
from pandas import DataFrame
|
|
import pandas._testing as tm
|
|
|
|
|
|
@pytest.fixture(params=[True, False])
|
|
def by_blocks_fixture(request):
|
|
return request.param
|
|
|
|
|
|
@pytest.fixture(params=["DataFrame", "Series"])
|
|
def obj_fixture(request):
|
|
return request.param
|
|
|
|
|
|
def _assert_frame_equal_both(a, b, **kwargs):
|
|
"""
|
|
Check that two DataFrame equal.
|
|
|
|
This check is performed commutatively.
|
|
|
|
Parameters
|
|
----------
|
|
a : DataFrame
|
|
The first DataFrame to compare.
|
|
b : DataFrame
|
|
The second DataFrame to compare.
|
|
kwargs : dict
|
|
The arguments passed to `tm.assert_frame_equal`.
|
|
"""
|
|
tm.assert_frame_equal(a, b, **kwargs)
|
|
tm.assert_frame_equal(b, a, **kwargs)
|
|
|
|
|
|
@pytest.mark.parametrize("check_like", [True, False])
|
|
def test_frame_equal_row_order_mismatch(check_like, obj_fixture):
|
|
df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"])
|
|
df2 = DataFrame({"A": [3, 2, 1], "B": [6, 5, 4]}, index=["c", "b", "a"])
|
|
|
|
if not check_like: # Do not ignore row-column orderings.
|
|
msg = f"{obj_fixture}.index are different"
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture)
|
|
else:
|
|
_assert_frame_equal_both(df1, df2, check_like=check_like, obj=obj_fixture)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"df1,df2",
|
|
[
|
|
(DataFrame({"A": [1, 2, 3]}), DataFrame({"A": [1, 2, 3, 4]})),
|
|
(DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}), DataFrame({"A": [1, 2, 3]})),
|
|
],
|
|
)
|
|
def test_frame_equal_shape_mismatch(df1, df2, obj_fixture):
|
|
msg = f"{obj_fixture} are different"
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, obj=obj_fixture)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"df1,df2,msg",
|
|
[
|
|
# Index
|
|
(
|
|
DataFrame.from_records({"a": [1, 2], "c": ["l1", "l2"]}, index=["a"]),
|
|
DataFrame.from_records({"a": [1.0, 2.0], "c": ["l1", "l2"]}, index=["a"]),
|
|
"DataFrame\\.index are different",
|
|
),
|
|
# MultiIndex
|
|
(
|
|
DataFrame.from_records(
|
|
{"a": [1, 2], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
|
|
),
|
|
DataFrame.from_records(
|
|
{"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
|
|
),
|
|
"MultiIndex level \\[0\\] are different",
|
|
),
|
|
],
|
|
)
|
|
def test_frame_equal_index_dtype_mismatch(df1, df2, msg, check_index_type):
|
|
kwargs = {"check_index_type": check_index_type}
|
|
|
|
if check_index_type:
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, **kwargs)
|
|
else:
|
|
tm.assert_frame_equal(df1, df2, **kwargs)
|
|
|
|
|
|
def test_empty_dtypes(check_dtype):
|
|
columns = ["col1", "col2"]
|
|
df1 = DataFrame(columns=columns)
|
|
df2 = DataFrame(columns=columns)
|
|
|
|
kwargs = {"check_dtype": check_dtype}
|
|
df1["col1"] = df1["col1"].astype("int64")
|
|
|
|
if check_dtype:
|
|
msg = r"Attributes of DataFrame\..* are different"
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, **kwargs)
|
|
else:
|
|
tm.assert_frame_equal(df1, df2, **kwargs)
|
|
|
|
|
|
@pytest.mark.parametrize("check_like", [True, False])
|
|
def test_frame_equal_index_mismatch(check_like, obj_fixture, using_infer_string):
|
|
if using_infer_string:
|
|
dtype = "string"
|
|
else:
|
|
dtype = "object"
|
|
msg = f"""{obj_fixture}\\.index are different
|
|
|
|
{obj_fixture}\\.index values are different \\(33\\.33333 %\\)
|
|
\\[left\\]: Index\\(\\['a', 'b', 'c'\\], dtype='{dtype}'\\)
|
|
\\[right\\]: Index\\(\\['a', 'b', 'd'\\], dtype='{dtype}'\\)
|
|
At positional index 2, first diff: c != d"""
|
|
|
|
df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"])
|
|
df2 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "d"])
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture)
|
|
|
|
|
|
@pytest.mark.parametrize("check_like", [True, False])
|
|
def test_frame_equal_columns_mismatch(check_like, obj_fixture, using_infer_string):
|
|
if using_infer_string:
|
|
dtype = "string"
|
|
else:
|
|
dtype = "object"
|
|
msg = f"""{obj_fixture}\\.columns are different
|
|
|
|
{obj_fixture}\\.columns values are different \\(50\\.0 %\\)
|
|
\\[left\\]: Index\\(\\['A', 'B'\\], dtype='{dtype}'\\)
|
|
\\[right\\]: Index\\(\\['A', 'b'\\], dtype='{dtype}'\\)"""
|
|
|
|
df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}, index=["a", "b", "c"])
|
|
df2 = DataFrame({"A": [1, 2, 3], "b": [4, 5, 6]}, index=["a", "b", "c"])
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, check_like=check_like, obj=obj_fixture)
|
|
|
|
|
|
def test_frame_equal_block_mismatch(by_blocks_fixture, obj_fixture):
|
|
obj = obj_fixture
|
|
msg = f"""{obj}\\.iloc\\[:, 1\\] \\(column name="B"\\) are different
|
|
|
|
{obj}\\.iloc\\[:, 1\\] \\(column name="B"\\) values are different \\(33\\.33333 %\\)
|
|
\\[index\\]: \\[0, 1, 2\\]
|
|
\\[left\\]: \\[4, 5, 6\\]
|
|
\\[right\\]: \\[4, 5, 7\\]"""
|
|
|
|
df1 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})
|
|
df2 = DataFrame({"A": [1, 2, 3], "B": [4, 5, 7]})
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, by_blocks=by_blocks_fixture, obj=obj_fixture)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"df1,df2,msg",
|
|
[
|
|
(
|
|
DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "ë"]}),
|
|
DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "e̊"]}),
|
|
"""{obj}\\.iloc\\[:, 1\\] \\(column name="E"\\) are different
|
|
|
|
{obj}\\.iloc\\[:, 1\\] \\(column name="E"\\) values are different \\(33\\.33333 %\\)
|
|
\\[index\\]: \\[0, 1, 2\\]
|
|
\\[left\\]: \\[é, è, ë\\]
|
|
\\[right\\]: \\[é, è, e̊\\]""",
|
|
),
|
|
(
|
|
DataFrame({"A": ["á", "à", "ä"], "E": ["é", "è", "ë"]}),
|
|
DataFrame({"A": ["a", "a", "a"], "E": ["e", "e", "e"]}),
|
|
"""{obj}\\.iloc\\[:, 0\\] \\(column name="A"\\) are different
|
|
|
|
{obj}\\.iloc\\[:, 0\\] \\(column name="A"\\) values are different \\(100\\.0 %\\)
|
|
\\[index\\]: \\[0, 1, 2\\]
|
|
\\[left\\]: \\[á, à, ä\\]
|
|
\\[right\\]: \\[a, a, a\\]""",
|
|
),
|
|
],
|
|
)
|
|
def test_frame_equal_unicode(df1, df2, msg, by_blocks_fixture, obj_fixture):
|
|
# see gh-20503
|
|
#
|
|
# Test ensures that `tm.assert_frame_equals` raises the right exception
|
|
# when comparing DataFrames containing differing unicode objects.
|
|
msg = msg.format(obj=obj_fixture)
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, by_blocks=by_blocks_fixture, obj=obj_fixture)
|
|
|
|
|
|
def test_assert_frame_equal_extension_dtype_mismatch():
|
|
# https://github.com/pandas-dev/pandas/issues/32747
|
|
left = DataFrame({"a": [1, 2, 3]}, dtype="Int64")
|
|
right = left.astype(int)
|
|
|
|
msg = (
|
|
"Attributes of DataFrame\\.iloc\\[:, 0\\] "
|
|
'\\(column name="a"\\) are different\n\n'
|
|
'Attribute "dtype" are different\n'
|
|
"\\[left\\]: Int64\n"
|
|
"\\[right\\]: int[32|64]"
|
|
)
|
|
|
|
tm.assert_frame_equal(left, right, check_dtype=False)
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(left, right, check_dtype=True)
|
|
|
|
|
|
def test_assert_frame_equal_interval_dtype_mismatch():
|
|
# https://github.com/pandas-dev/pandas/issues/32747
|
|
left = DataFrame({"a": [pd.Interval(0, 1)]}, dtype="interval")
|
|
right = left.astype(object)
|
|
|
|
msg = (
|
|
"Attributes of DataFrame\\.iloc\\[:, 0\\] "
|
|
'\\(column name="a"\\) are different\n\n'
|
|
'Attribute "dtype" are different\n'
|
|
"\\[left\\]: interval\\[int64, right\\]\n"
|
|
"\\[right\\]: object"
|
|
)
|
|
|
|
tm.assert_frame_equal(left, right, check_dtype=False)
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(left, right, check_dtype=True)
|
|
|
|
|
|
def test_assert_frame_equal_ignore_extension_dtype_mismatch():
|
|
# https://github.com/pandas-dev/pandas/issues/35715
|
|
left = DataFrame({"a": [1, 2, 3]}, dtype="Int64")
|
|
right = DataFrame({"a": [1, 2, 3]}, dtype="Int32")
|
|
tm.assert_frame_equal(left, right, check_dtype=False)
|
|
|
|
|
|
def test_assert_frame_equal_ignore_extension_dtype_mismatch_cross_class():
|
|
# https://github.com/pandas-dev/pandas/issues/35715
|
|
left = DataFrame({"a": [1, 2, 3]}, dtype="Int64")
|
|
right = DataFrame({"a": [1, 2, 3]}, dtype="int64")
|
|
tm.assert_frame_equal(left, right, check_dtype=False)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"dtype",
|
|
[
|
|
("timedelta64[ns]"),
|
|
("datetime64[ns, UTC]"),
|
|
("Period[D]"),
|
|
],
|
|
)
|
|
def test_assert_frame_equal_datetime_like_dtype_mismatch(dtype):
|
|
df1 = DataFrame({"a": []}, dtype=dtype)
|
|
df2 = DataFrame({"a": []})
|
|
tm.assert_frame_equal(df1, df2, check_dtype=False)
|
|
|
|
|
|
def test_allows_duplicate_labels():
|
|
left = DataFrame()
|
|
right = DataFrame().set_flags(allows_duplicate_labels=False)
|
|
tm.assert_frame_equal(left, left)
|
|
tm.assert_frame_equal(right, right)
|
|
tm.assert_frame_equal(left, right, check_flags=False)
|
|
tm.assert_frame_equal(right, left, check_flags=False)
|
|
|
|
with pytest.raises(AssertionError, match="<Flags"):
|
|
tm.assert_frame_equal(left, right)
|
|
|
|
with pytest.raises(AssertionError, match="<Flags"):
|
|
tm.assert_frame_equal(left, right)
|
|
|
|
|
|
def test_assert_frame_equal_columns_mixed_dtype():
|
|
# GH#39168
|
|
df = DataFrame([[0, 1, 2]], columns=["foo", "bar", 42], index=[1, "test", 2])
|
|
tm.assert_frame_equal(df, df, check_like=True)
|
|
|
|
|
|
def test_frame_equal_extension_dtype(frame_or_series, any_numeric_ea_dtype):
|
|
# GH#39410
|
|
obj = frame_or_series([1, 2], dtype=any_numeric_ea_dtype)
|
|
tm.assert_equal(obj, obj, check_exact=True)
|
|
|
|
|
|
@pytest.mark.parametrize("indexer", [(0, 1), (1, 0)])
|
|
def test_frame_equal_mixed_dtypes(frame_or_series, any_numeric_ea_dtype, indexer):
|
|
dtypes = (any_numeric_ea_dtype, "int64")
|
|
obj1 = frame_or_series([1, 2], dtype=dtypes[indexer[0]])
|
|
obj2 = frame_or_series([1, 2], dtype=dtypes[indexer[1]])
|
|
tm.assert_equal(obj1, obj2, check_exact=True, check_dtype=False)
|
|
|
|
|
|
def test_assert_frame_equal_check_like_different_indexes():
|
|
# GH#39739
|
|
df1 = DataFrame(index=pd.Index([], dtype="object"))
|
|
df2 = DataFrame(index=pd.RangeIndex(start=0, stop=0, step=1))
|
|
with pytest.raises(AssertionError, match="DataFrame.index are different"):
|
|
tm.assert_frame_equal(df1, df2, check_like=True)
|
|
|
|
|
|
def test_assert_frame_equal_checking_allow_dups_flag():
|
|
# GH#45554
|
|
left = DataFrame([[1, 2], [3, 4]])
|
|
left.flags.allows_duplicate_labels = False
|
|
|
|
right = DataFrame([[1, 2], [3, 4]])
|
|
right.flags.allows_duplicate_labels = True
|
|
tm.assert_frame_equal(left, right, check_flags=False)
|
|
|
|
with pytest.raises(AssertionError, match="allows_duplicate_labels"):
|
|
tm.assert_frame_equal(left, right, check_flags=True)
|
|
|
|
|
|
def test_assert_frame_equal_check_like_categorical_midx():
|
|
# GH#48975
|
|
left = DataFrame(
|
|
[[1], [2], [3]],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[
|
|
pd.Categorical(["a", "b", "c"]),
|
|
pd.Categorical(["a", "b", "c"]),
|
|
]
|
|
),
|
|
)
|
|
right = DataFrame(
|
|
[[3], [2], [1]],
|
|
index=pd.MultiIndex.from_arrays(
|
|
[
|
|
pd.Categorical(["c", "b", "a"]),
|
|
pd.Categorical(["c", "b", "a"]),
|
|
]
|
|
),
|
|
)
|
|
tm.assert_frame_equal(left, right, check_like=True)
|
|
|
|
|
|
def test_assert_frame_equal_ea_column_definition_in_exception_mask():
|
|
# GH#50323
|
|
df1 = DataFrame({"a": pd.Series([pd.NA, 1], dtype="Int64")})
|
|
df2 = DataFrame({"a": pd.Series([1, 1], dtype="Int64")})
|
|
|
|
msg = r'DataFrame.iloc\[:, 0\] \(column name="a"\) NA mask values are different'
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2)
|
|
|
|
|
|
def test_assert_frame_equal_ea_column_definition_in_exception():
|
|
# GH#50323
|
|
df1 = DataFrame({"a": pd.Series([pd.NA, 1], dtype="Int64")})
|
|
df2 = DataFrame({"a": pd.Series([pd.NA, 2], dtype="Int64")})
|
|
|
|
msg = r'DataFrame.iloc\[:, 0\] \(column name="a"\) values are different'
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2)
|
|
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2, check_exact=True)
|
|
|
|
|
|
def test_assert_frame_equal_ts_column():
|
|
# GH#50323
|
|
df1 = DataFrame({"a": [pd.Timestamp("2019-12-31"), pd.Timestamp("2020-12-31")]})
|
|
df2 = DataFrame({"a": [pd.Timestamp("2020-12-31"), pd.Timestamp("2020-12-31")]})
|
|
|
|
msg = r'DataFrame.iloc\[:, 0\] \(column name="a"\) values are different'
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2)
|
|
|
|
|
|
def test_assert_frame_equal_set():
|
|
# GH#51727
|
|
df1 = DataFrame({"set_column": [{1, 2, 3}, {4, 5, 6}]})
|
|
df2 = DataFrame({"set_column": [{1, 2, 3}, {4, 5, 6}]})
|
|
tm.assert_frame_equal(df1, df2)
|
|
|
|
|
|
def test_assert_frame_equal_set_mismatch():
|
|
# GH#51727
|
|
df1 = DataFrame({"set_column": [{1, 2, 3}, {4, 5, 6}]})
|
|
df2 = DataFrame({"set_column": [{1, 2, 3}, {4, 5, 7}]})
|
|
|
|
msg = r'DataFrame.iloc\[:, 0\] \(column name="set_column"\) values are different'
|
|
with pytest.raises(AssertionError, match=msg):
|
|
tm.assert_frame_equal(df1, df2)
|