def make_table(x,y,allStates):
    x0, y0, x1, y1, x2, y2, trnums0, trnums1, trnums2 = getTrackPiecesForInfo(x, y, allStates)
    
    numPmsd = 4
    numPmss = 4
    p = np.linspace(0.5, 6, 12)
    
    info = []
    i = 0
    for xx, yy, tn in zip(x0 + x1 + x2, y0 + y1 + y2, trnums0 + trnums1 + trnums2):
        lx = len(xx)
        st = 0 + (i >= len(x0)) * 1 + (i >= len(x0 + x1)) * 1
    
        closest = min(indices, key = lambda x:abs(x-int(np.floor(tn))))
        cn = ((closest - int(np.floor(tn))) < 0) * indices.index(closest) + \
        ((closest - int(np.floor(tn))) > 0) * (indices.index(closest) - 1)
    
        if len(xx) > max(numPmsd, numPmss):
            dif, _, smss, _ = getMSDandMSS([xx], [yy], numPmsd, numPmss, p)
        else:
            dif = 'NA'
            smss = 'NA'
    
        info.append([st, cn, tn, lx, dif, smss])
        i = i +1 
    
    colSt = [i[0] for i in info]
    colCn = [i[1] for i in info]
    colTn = [i[2] for i in info]
    colLx = [i[3] for i in info]
    colDi = [i[4] for i in info]
    colSm = [i[5] for i in info]
    
    df = pd.DataFrame({'State' : colSt, \
                       'Cell number' : colCn, \
                       'Track number': colTn, \
                       'Tracklet length': colLx, \
                       'Diffusion constant': colDi, \
                       'Smss': colSm})
    
    dfSorted = df.sort_values(by=['Track number'])
    dfSorted.columns.names = ['Tracklet number']
    
    return dfSorted