You might want to consider using kernel density plots rather than histograms, as histograms exhibit aliasing artifacts.

In general, binning/bucketing can be seen as filtering the empirical density function of your dataset with a box filter and then sampling. The frequency response of a box filter is the sinc function, which has a lot of energy above the Nyquist of this sampling rate. Kernel density plots with a gaussian kernel, on the other hand, can be seen as filtering the empirical density function with a gaussian filter and are thus approximately bandlimited.