code: def gausspars(data):
      
      N, mean, d = len(data), 0., 0.
      if N < 1:
          return "", ""
      if N == 1:
          return data[0], 0
      for j in range(N):
          mean += old_div(data[j], float(N))
      for j in range(N):
          d += (data[j] - mean)**2
      stdev = np.sqrt(d * (1./(float(N - 1))))
      return mean, stdev
docs: calculates gaussian statistics for data