Mark Dickinson <dicki...@gmail.com> added the comment: > then the answer being 90 is correct,right?
How do you deduce that? Why 90 rather than 85 (or 87.5, or some other value)? For what it's worth, NumPy gives a result of NaN for the median of an array that contains NaNs: >>> np.median([1.0, 2.0, 3.0, np.nan]) /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/function_base.py:4033: RuntimeWarning: Invalid value encountered in median r = func(a, **kwargs) nan ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue33084> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
