def binfunctionII(stuff, binwidth):
    B = stuff[:,4]
    bins=np.linspace(min(B), max(B)+binwidth,
                            ((max(B)+binwidth)-min(B))/binwidth)
    out = []
    for i in range(len(bins)-1):
        temp=(B>=bins[i])&(B<bins[i+1])
        out.append(stuff[temp])
    return out

for t in range(len(alldata)):
    certaindata = alldata[t]
    print t
    Vdata = certaindata[np.argsort(certaindata[:, 4])]
    print Vdata
    Vdatavals = list(binfunctionII(Vdata, 1))

[array([[  12.11974609,   13.4       ,   63.4       ,    4.1       ,
     129.98302733,   37.30872341]]),
 array([], shape=(0L, 6L), dtype=float64),
 array([], shape=(0L, 6L), dtype=float64),
 array([], shape=(0L, 6L), dtype=float64),
 array([[  13.78698792,   16.12224827,   59.        ,    4.1       ,
     174.01460895,   44.40542507]]),...]

[[12.11974609, 13.4, 63.4, 4.1, 129.98302733, 37.30872341],
 [13.78698792, 16.12224827, 59., 4.1, 174.01460895, 44.40542507],...]

Vdatavals = np.ndarray(binfunctionII(Vdata, 1)).tolist()

    ValueError: sequence too large; must be smaller than 32

VdatavalsNONZERO = [x for x in Vdatavals if x != []]

    #But this literally changes nothing

VdatavalsNONZERO = filter(None, Vdata)

    ValueError: The truth value of an array with more than one element is ambiguous.
    Use a.any() or a.all()