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DOC: Clarify the magnitude for truncation (#60976)
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doc/source/user_guide/window.rst

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@@ -70,7 +70,8 @@ which will first group the data by the specified keys and then perform a windowi
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Some windowing aggregation, ``mean``, ``sum``, ``var`` and ``std`` methods may suffer from numerical
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imprecision due to the underlying windowing algorithms accumulating sums. When values differ
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with magnitude :math:`1/np.finfo(np.double).eps` this results in truncation. It must be
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with magnitude ``1/np.finfo(np.double).eps`` (approximately :math:`4.5 \times 10^{15}`),
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this results in truncation. It must be
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noted, that large values may have an impact on windows, which do not include these values. `Kahan summation
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<https://en.wikipedia.org/wiki/Kahan_summation_algorithm>`__ is used
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to compute the rolling sums to preserve accuracy as much as possible.

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