Data binning

Data binning, also called data discrete binning or data bucketing, is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall into a given small interval, a bin, are replaced by a value representative of that interval, often a central value (mean or median).^{[citation needed]} It is related to quantization: data binning operates on the abscissa axis while quantization operates on the ordinate axis. Binning is a generalization of rounding.

Statistical data binning is a way to group numbers of more-or-less continuous values into a smaller number of "bins". For example, if you have data about a group of people, you might want to arrange their ages into a smaller number of age intervals (for example, grouping every five years together). It can also be used in multivariate statistics, binning in several dimensions at once.

In digital image processing, "binning" has a very different meaning. Pixel binning is the process of combining blocks of adjacent pixels throughout an image, by summing or averaging their values, during or after readout. It reduces the amount of data; also the relative noise level in the result is lower.