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I want to get a list of the data contained in a histogram bin. I am using numpy, and Matplotlib. I know how to traverse the data and check the bin edges. However, I want to do this for a 2D histogram and the code to do this is rather ugly. Does numpy have any constructs to make this easier? For the 1D case, I can use searchsorted(). But the logic is not that much better, and I don’t really want to do a binary search on each data point when I don’t have to. Most of the nasty logic is due to the bin boundary regions. All regions have boundaries like this: [left edge, right edge). Except the last bin, which has a region like this: [left edge, right edge]. Here is some sample code for the 1D case: import numpy as np data = [0, 0.5, 1.5, 1.5, 1.5, 2.5, 2.5, 2.5, 3] hist, edges = np.histogram(data, bins=3) print 'data =', data print 'histogram =', hist print 'edges =', edges getbin = 2 #0, 1, or 2 print '---' print 'alg 1:' #for i in range(len(data)): for d in data: if d >= edges[getbin]: if (getbin == len(edges)-2) or d < edges[getbin+1]: print 'found:', d #end if #end if #end for print '---' print 'alg 2:' for d in data: val = np.searchsorted(edges, d, side='right')-1 if val == getbin or val == len(edges)-1: print 'found:', d #end if #end for Here is some sample code for the 2D case: import numpy as np xdata = [0, 1.5, 1.5, 2.5, 2.5, 2.5, \ 0.5, 0.5, 0.5, 0.5, 1.5, 1.5, 1.5, 1.5, 1.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, \ 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 1.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 3] ydata = [0, 5,5, 5, 5, 5, \ 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, \ 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 30] xbins = 3 ybins = 3 hist2d, xedges, yedges = np.histogram2d(xdata,

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