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Fix variance calculation for complex numbers by preserving dtype #62555
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ser2 = Series([1 + 2j, 2 + 3j, 3 + 4j], dtype=np.complex128) | ||
expected_var = 2.0 | ||
tm.assert_almost_equal(ser2.var(ddof=1), expected_var) |
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Do we need assert_almost_equal
or can we use assert_series_equal
?
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We need assert_almost_equal because .var() will return a scalar not a series
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Can you instead adjust the expected
value to be the right type of output? The point of assert_almost_equal
is to allow for differences in precision, but not necessarily in types
ser2.var(ddof=1), np.var([1 + 2j, 2 + 3j, 3 + 4j], ddof=1) | ||
) | ||
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# Test with NaN |
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Rather than creating multiple variables it would be better to parametrize the inputs to this test
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added the inputs as parameters
# Test other ddof values | ||
tm.assert_almost_equal(ser2.var(ddof=0), 4 / 3) | ||
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# Test that imaginary part is preserved in mean calculation |
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This looks like it should be a separate test
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made this a separate test
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doc/source/whatsnew/vX.X.X.rst
file if fixing a bug or adding a new feature.