array = [1.0, 1.2, 0.4, ...] # A bunch of numbers
counts = {}
for a in array:
  if a in counts:
    counts[a] += 1
  else:
    counts[a] = 1

sorted([(v, k) for k, v in counts.items()])[-1][1]

NB. random array of floating-point numbers
   ] y =: 10 (?@$%]) 5
0 0.6 0.2 0.4 0.4 0.8 0.6 0.6 0.8 0
   NB. count occurrences
   ({:,#)/.~ y
  0 2
0.6 3
0.2 1
0.4 2
0.8 2
   NB. order by occurrences
   (:{:"1)({:,#)/.~ y
0.6 3
  0 2
0.4 2
0.8 2
0.2 1
   NB. pick the most frequent
   {.{.(:{:"1)({:,#)/.~ y
0.6

epsilon = 0.0001
def almost_equal(a, b):
    return -epsilon <= a-b <= epsilon

array = [0.0, 0.6, 0.2, 0.4, 0.4, 0.8, 0.6, 0.6, 0.8, 0.0]

# more efficient would be to keep this in sorted order,
# and use binary search to determine where to insert,
# but this is just a simple demo
counts = []
for a in array:
    for i, (b, c) in enumerate(counts):
        if almost_equal(a, b):
            counts[i] = (b, c + 1)
            break
    else:
        counts.append((a, 1))

# sort by frequency, extract key of most frequent
print "Mode is %f" % sorted(counts, key = lambda(a, b): b)[-1][0]