Steven D'Aprano added the comment: On Tue, Dec 13, 2016 at 09:35:22AM +0000, Srikanth Anantharam wrote: > > Srikanth Anantharam added the comment: > > A better choice would be to return a tuple of values (sliced from the > table). And let the user decide which one to use.
The current mode() function is designed for a very basic use-case, where you have an obvious single mode from discrete data. The problem with dealing with multiple modes is that its not easy to tell the difference between a genuinely multi-modal sample and one which just happens to have a few samples with the same value: data = [1, 2, 3, 4, 4, 4, 5, 6, 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 9] Assuming the sampling is fair, 8 is clearly the mode; but is it bimodal with 4 the second mode? Or perhaps even four modes, 8, 4, 7 and 9? I have plans for introducing a binning function to collect data into bins and run statistics on the bins. That might be a better way to deal with multi-modal samples: if you bin the data (for discrete data, use a bin size of 1) and then look at the frequencies, you can decide how many modes there are. Thanks for the suggestion. ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue28956> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
