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Can anybody reading this comment please enlighten me on good algorithms for optimum bin sizes for histograms? I have tried DW Scott's (1979) method. But are there any new better kid in the block?

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I'm by no means an expert in the area, but i know that the Freedman-Diaconis rule (https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule) is used by the seaborn Python plotting library (https://web.stanford.edu/~mwaskom/software/seaborn/index.htm...) which seems to consistently produce good results.

There is no free lunch. You must know something about your data -- use your intuition.

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