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November 23, 2018 17:58
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Compute the recommended bin size for a histogram, according to the Freedman-Diaconis rule
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| def bin_size(x): | |
| """ | |
| https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule | |
| """ | |
| return (2 * (np.nanquantile(x, 0.75) - np.nanquantile(x, 0.25)) / | |
| np.cbrt(len(x[~np.isnan(x)]))) |
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the quantiles are in the wrong order :)