This is one way to do it.
from mpl_toolkits.mplot3d import Axes3D
from scipy.interpolate import griddata
import matplotlib.pyplot as plt
import numpy as np
data = [(60, 5, '121'), (61, 5, '103'), (62, 5, '14.8'), (63, 5, '48.5'), (64, 5, '57.5'), (65, 5, '75.7'), (66, 5, '89.6'), (67, 5, '55.3'), (68, 5, '63.3'), (69, 5, '118'), (70, 5, '128'), (71, 5, '105'), (72, 5, '115'), (73, 5, '104'), (74, 5, '134'), (75, 5, '123'), (76, 5, '66.3'), (77, 5, '132'), (78, 5, '145'), (79, 5, '115'), (80, 5, '38.2'), (81, 5, '10.4'), (82, 5, '18.4'), (83, 5, '87'), (84, 5, '86.7'), (85, 5, '78.9'), (86, 5, '89.9'), (87, 5, '108'), (88, 5, '57.1'), (89, 5, '51.1'), (90, 5, '69.1'), (91, 5, '59.8'), (60, 6, '48.9'), (61, 6, '33.3'), (62, 6, '-19.2'), (63, 6, '-17.5'), (64, 6, '-6.5'), (65, 6, '75.7'), (66, 6, '89.6'), (67, 6, '55.3'), (68, 6, '99.8'), (69, 6, '156'), (70, 6, '141'), (71, 6, '54.1'), (72, 6, '66.1'), (73, 6, '98.9'), (74, 6, '155'), (75, 6, '146'), (76, 6, '111'), (77, 6, '132'), (78, 6, '145'), (79, 6, '97.3'), (80, 6, '101'), (81, 6, '59.4'), (82, 6, '70.4'), (83, 6, '142'), (84, 6, '145'), (85, 6, '140'), (86, 6, '56.9'), (87, 6, '77.8'), (88, 6, '21.1'), (89, 6, '27.1'), (90, 6, '48.1'), (91, 6, '41.8')]
x, y, z = zip(*data)
z = map(float, z)
grid_x, grid_y = np.mgrid[min(x):max(x):100j, min(y):max(y):100j]
grid_z = griddata((x, y), z, (grid_x, grid_y), method='cubic')
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_surface(grid_x, grid_y, grid_z, cmap=plt.cm.Spectral)
plt.show()