425 lines
13 KiB
Python
425 lines
13 KiB
Python
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import numpy as np
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import pytest
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import pandas as pd
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from pandas import (
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Categorical,
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DataFrame,
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Series,
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)
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import pandas._testing as tm
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def _assert_series_equal_both(a, b, **kwargs):
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"""
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Check that two Series equal.
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This check is performed commutatively.
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Parameters
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----------
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a : Series
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The first Series to compare.
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b : Series
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The second Series to compare.
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kwargs : dict
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The arguments passed to `tm.assert_series_equal`.
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"""
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tm.assert_series_equal(a, b, **kwargs)
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tm.assert_series_equal(b, a, **kwargs)
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def _assert_not_series_equal(a, b, **kwargs):
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"""
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Check that two Series are not equal.
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Parameters
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----------
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a : Series
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The first Series to compare.
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b : Series
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The second Series to compare.
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kwargs : dict
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The arguments passed to `tm.assert_series_equal`.
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"""
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try:
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tm.assert_series_equal(a, b, **kwargs)
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msg = "The two Series were equal when they shouldn't have been"
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pytest.fail(msg=msg)
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except AssertionError:
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pass
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def _assert_not_series_equal_both(a, b, **kwargs):
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"""
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Check that two Series are not equal.
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This check is performed commutatively.
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Parameters
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----------
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a : Series
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The first Series to compare.
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b : Series
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The second Series to compare.
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kwargs : dict
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The arguments passed to `tm.assert_series_equal`.
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"""
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_assert_not_series_equal(a, b, **kwargs)
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_assert_not_series_equal(b, a, **kwargs)
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@pytest.mark.parametrize("data", [range(3), list("abc"), list("áàä")])
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def test_series_equal(data):
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_assert_series_equal_both(Series(data), Series(data))
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@pytest.mark.parametrize(
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"data1,data2",
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[
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(range(3), range(1, 4)),
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(list("abc"), list("xyz")),
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(list("áàä"), list("éèë")),
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(list("áàä"), list(b"aaa")),
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(range(3), range(4)),
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],
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)
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def test_series_not_equal_value_mismatch(data1, data2):
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_assert_not_series_equal_both(Series(data1), Series(data2))
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@pytest.mark.parametrize(
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"kwargs",
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[
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{"dtype": "float64"}, # dtype mismatch
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{"index": [1, 2, 4]}, # index mismatch
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{"name": "foo"}, # name mismatch
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],
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)
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def test_series_not_equal_metadata_mismatch(kwargs):
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data = range(3)
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s1 = Series(data)
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s2 = Series(data, **kwargs)
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_assert_not_series_equal_both(s1, s2)
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@pytest.mark.parametrize("data1,data2", [(0.12345, 0.12346), (0.1235, 0.1236)])
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@pytest.mark.parametrize("dtype", ["float32", "float64", "Float32"])
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@pytest.mark.parametrize("decimals", [0, 1, 2, 3, 5, 10])
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def test_less_precise(data1, data2, dtype, decimals):
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rtol = 10**-decimals
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s1 = Series([data1], dtype=dtype)
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s2 = Series([data2], dtype=dtype)
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if decimals in (5, 10) or (decimals >= 3 and abs(data1 - data2) >= 0.0005):
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msg = "Series values are different"
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, rtol=rtol)
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else:
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_assert_series_equal_both(s1, s2, rtol=rtol)
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@pytest.mark.parametrize(
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"s1,s2,msg",
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[
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# Index
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(
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Series(["l1", "l2"], index=[1, 2]),
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Series(["l1", "l2"], index=[1.0, 2.0]),
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"Series\\.index are different",
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),
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# MultiIndex
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(
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DataFrame.from_records(
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{"a": [1, 2], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
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).c,
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DataFrame.from_records(
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{"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
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).c,
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"MultiIndex level \\[0\\] are different",
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),
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],
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)
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def test_series_equal_index_dtype(s1, s2, msg, check_index_type):
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kwargs = {"check_index_type": check_index_type}
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if check_index_type:
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, **kwargs)
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else:
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tm.assert_series_equal(s1, s2, **kwargs)
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@pytest.mark.parametrize("check_like", [True, False])
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def test_series_equal_order_mismatch(check_like):
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s1 = Series([1, 2, 3], index=["a", "b", "c"])
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s2 = Series([3, 2, 1], index=["c", "b", "a"])
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if not check_like: # Do not ignore index ordering.
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with pytest.raises(AssertionError, match="Series.index are different"):
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tm.assert_series_equal(s1, s2, check_like=check_like)
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else:
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_assert_series_equal_both(s1, s2, check_like=check_like)
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@pytest.mark.parametrize("check_index", [True, False])
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def test_series_equal_index_mismatch(check_index):
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s1 = Series([1, 2, 3], index=["a", "b", "c"])
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s2 = Series([1, 2, 3], index=["c", "b", "a"])
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if check_index: # Do not ignore index.
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with pytest.raises(AssertionError, match="Series.index are different"):
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tm.assert_series_equal(s1, s2, check_index=check_index)
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else:
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_assert_series_equal_both(s1, s2, check_index=check_index)
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def test_series_invalid_param_combination():
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left = Series(dtype=object)
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right = Series(dtype=object)
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with pytest.raises(
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ValueError, match="check_like must be False if check_index is False"
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):
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tm.assert_series_equal(left, right, check_index=False, check_like=True)
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def test_series_equal_length_mismatch(rtol):
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msg = """Series are different
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Series length are different
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\\[left\\]: 3, RangeIndex\\(start=0, stop=3, step=1\\)
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\\[right\\]: 4, RangeIndex\\(start=0, stop=4, step=1\\)"""
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s1 = Series([1, 2, 3])
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s2 = Series([1, 2, 3, 4])
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, rtol=rtol)
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def test_series_equal_numeric_values_mismatch(rtol):
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msg = """Series are different
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Series values are different \\(33\\.33333 %\\)
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\\[index\\]: \\[0, 1, 2\\]
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\\[left\\]: \\[1, 2, 3\\]
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\\[right\\]: \\[1, 2, 4\\]"""
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s1 = Series([1, 2, 3])
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s2 = Series([1, 2, 4])
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, rtol=rtol)
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def test_series_equal_categorical_values_mismatch(rtol):
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msg = """Series are different
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Series values are different \\(66\\.66667 %\\)
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\\[index\\]: \\[0, 1, 2\\]
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\\[left\\]: \\['a', 'b', 'c'\\]
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Categories \\(3, object\\): \\['a', 'b', 'c'\\]
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\\[right\\]: \\['a', 'c', 'b'\\]
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Categories \\(3, object\\): \\['a', 'b', 'c'\\]"""
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s1 = Series(Categorical(["a", "b", "c"]))
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s2 = Series(Categorical(["a", "c", "b"]))
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, rtol=rtol)
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def test_series_equal_datetime_values_mismatch(rtol):
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msg = """Series are different
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Series values are different \\(100.0 %\\)
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\\[index\\]: \\[0, 1, 2\\]
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\\[left\\]: \\[1514764800000000000, 1514851200000000000, 1514937600000000000\\]
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\\[right\\]: \\[1549065600000000000, 1549152000000000000, 1549238400000000000\\]"""
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s1 = Series(pd.date_range("2018-01-01", periods=3, freq="D"))
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s2 = Series(pd.date_range("2019-02-02", periods=3, freq="D"))
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, rtol=rtol)
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def test_series_equal_categorical_mismatch(check_categorical):
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msg = """Attributes of Series are different
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Attribute "dtype" are different
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\\[left\\]: CategoricalDtype\\(categories=\\['a', 'b'\\], ordered=False\\)
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\\[right\\]: CategoricalDtype\\(categories=\\['a', 'b', 'c'\\], \
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ordered=False\\)"""
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s1 = Series(Categorical(["a", "b"]))
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s2 = Series(Categorical(["a", "b"], categories=list("abc")))
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if check_categorical:
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s2, check_categorical=check_categorical)
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else:
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_assert_series_equal_both(s1, s2, check_categorical=check_categorical)
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def test_assert_series_equal_extension_dtype_mismatch():
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# https://github.com/pandas-dev/pandas/issues/32747
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left = Series(pd.array([1, 2, 3], dtype="Int64"))
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right = left.astype(int)
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msg = """Attributes of Series are different
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Attribute "dtype" are different
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\\[left\\]: Int64
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\\[right\\]: int[32|64]"""
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tm.assert_series_equal(left, right, check_dtype=False)
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(left, right, check_dtype=True)
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def test_assert_series_equal_interval_dtype_mismatch():
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# https://github.com/pandas-dev/pandas/issues/32747
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left = Series([pd.Interval(0, 1)], dtype="interval")
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right = left.astype(object)
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msg = """Attributes of Series are different
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Attribute "dtype" are different
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\\[left\\]: interval\\[int64, right\\]
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\\[right\\]: object"""
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tm.assert_series_equal(left, right, check_dtype=False)
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(left, right, check_dtype=True)
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def test_series_equal_series_type():
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class MySeries(Series):
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pass
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s1 = Series([1, 2])
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s2 = Series([1, 2])
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s3 = MySeries([1, 2])
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tm.assert_series_equal(s1, s2, check_series_type=False)
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tm.assert_series_equal(s1, s2, check_series_type=True)
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tm.assert_series_equal(s1, s3, check_series_type=False)
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tm.assert_series_equal(s3, s1, check_series_type=False)
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with pytest.raises(AssertionError, match="Series classes are different"):
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tm.assert_series_equal(s1, s3, check_series_type=True)
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with pytest.raises(AssertionError, match="Series classes are different"):
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tm.assert_series_equal(s3, s1, check_series_type=True)
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def test_series_equal_exact_for_nonnumeric():
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# https://github.com/pandas-dev/pandas/issues/35446
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s1 = Series(["a", "b"])
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s2 = Series(["a", "b"])
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s3 = Series(["b", "a"])
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tm.assert_series_equal(s1, s2, check_exact=True)
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tm.assert_series_equal(s2, s1, check_exact=True)
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msg = """Series are different
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Series values are different \\(100\\.0 %\\)
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\\[index\\]: \\[0, 1\\]
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\\[left\\]: \\[a, b\\]
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\\[right\\]: \\[b, a\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s1, s3, check_exact=True)
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msg = """Series are different
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Series values are different \\(100\\.0 %\\)
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\\[index\\]: \\[0, 1\\]
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\\[left\\]: \\[b, a\\]
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\\[right\\]: \\[a, b\\]"""
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with pytest.raises(AssertionError, match=msg):
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tm.assert_series_equal(s3, s1, check_exact=True)
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@pytest.mark.parametrize("right_dtype", ["Int32", "int64"])
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def test_assert_series_equal_ignore_extension_dtype_mismatch(right_dtype):
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# https://github.com/pandas-dev/pandas/issues/35715
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left = Series([1, 2, 3], dtype="Int64")
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right = Series([1, 2, 3], dtype=right_dtype)
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|
tm.assert_series_equal(left, right, check_dtype=False)
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||
|
|
|
||
|
|
|
||
|
|
def test_allows_duplicate_labels():
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||
|
|
left = Series([1])
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||
|
|
right = Series([1]).set_flags(allows_duplicate_labels=False)
|
||
|
|
tm.assert_series_equal(left, left)
|
||
|
|
tm.assert_series_equal(right, right)
|
||
|
|
tm.assert_series_equal(left, right, check_flags=False)
|
||
|
|
tm.assert_series_equal(right, left, check_flags=False)
|
||
|
|
|
||
|
|
with pytest.raises(AssertionError, match="<Flags"):
|
||
|
|
tm.assert_series_equal(left, right)
|
||
|
|
|
||
|
|
with pytest.raises(AssertionError, match="<Flags"):
|
||
|
|
tm.assert_series_equal(left, right)
|
||
|
|
|
||
|
|
|
||
|
|
def test_assert_series_equal_identical_na(nulls_fixture):
|
||
|
|
ser = Series([nulls_fixture])
|
||
|
|
|
||
|
|
tm.assert_series_equal(ser, ser.copy())
|
||
|
|
|
||
|
|
# while we're here do Index too
|
||
|
|
idx = pd.Index(ser)
|
||
|
|
tm.assert_index_equal(idx, idx.copy(deep=True))
|
||
|
|
|
||
|
|
|
||
|
|
def test_identical_nested_series_is_equal():
|
||
|
|
# GH#22400
|
||
|
|
x = Series(
|
||
|
|
[
|
||
|
|
0,
|
||
|
|
0.0131142231938,
|
||
|
|
1.77774652865e-05,
|
||
|
|
np.array([0.4722720840328748, 0.4216929783681722]),
|
||
|
|
]
|
||
|
|
)
|
||
|
|
y = Series(
|
||
|
|
[
|
||
|
|
0,
|
||
|
|
0.0131142231938,
|
||
|
|
1.77774652865e-05,
|
||
|
|
np.array([0.4722720840328748, 0.4216929783681722]),
|
||
|
|
]
|
||
|
|
)
|
||
|
|
# These two arrays should be equal, nesting could cause issue
|
||
|
|
|
||
|
|
tm.assert_series_equal(x, x)
|
||
|
|
tm.assert_series_equal(x, x, check_exact=True)
|
||
|
|
tm.assert_series_equal(x, y)
|
||
|
|
tm.assert_series_equal(x, y, check_exact=True)
|
||
|
|
|
||
|
|
|
||
|
|
@pytest.mark.parametrize("dtype", ["datetime64", "timedelta64"])
|
||
|
|
def test_check_dtype_false_different_reso(dtype):
|
||
|
|
# GH 52449
|
||
|
|
ser_s = Series([1000213, 2131232, 21312331]).astype(f"{dtype}[s]")
|
||
|
|
ser_ms = ser_s.astype(f"{dtype}[ms]")
|
||
|
|
with pytest.raises(AssertionError, match="Attributes of Series are different"):
|
||
|
|
tm.assert_series_equal(ser_s, ser_ms)
|
||
|
|
tm.assert_series_equal(ser_ms, ser_s, check_dtype=False)
|
||
|
|
|
||
|
|
ser_ms -= Series([1, 1, 1]).astype(f"{dtype}[ms]")
|
||
|
|
|
||
|
|
with pytest.raises(AssertionError, match="Series are different"):
|
||
|
|
tm.assert_series_equal(ser_s, ser_ms)
|
||
|
|
|
||
|
|
with pytest.raises(AssertionError, match="Series are different"):
|
||
|
|
tm.assert_series_equal(ser_s, ser_ms, check_dtype=False)
|