3D plot in python from a csv file

import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from scipy.interpolate import griddata

Dim2	Dim1	Dim3
5	1	109.582
5	2	105.657
5	3	113.476
5	4	107.209
5	5	104.784
5	6	102.218
5	7	100.377
5	8	104.111
5	9	69.258
5	10	59.227
5	11	47.046
5	12	37.144
5	13	27.968
5	14	25.118
5	15	21
5	16	18.444
5	17	19.306
5	18	9.637
5	19	4.066
5	20	0.06
4	1	158.586
4	2	153.183
4	3	160.387
4	4	153.693
4	5	150.667
4	6	145.106
4	7	142.821
4	8	149.522
4	9	109.88
4	10	97.388
4	11	81.012
4	12	67.986
4	13	58.08
4	14	53.754
4	15	48.378
4	16	45.452
4	17	43.249
4	18	27.168
4	19	17.932
4	20	0.302
3	1	215.783
3	2	207.373
3	3	215.219
3	4	209.206
3	5	205.631
3	6	198.287
3	7	196.91
3	8	204.884
3	9	163.378
3	10	149.805
3	11	132.181
3	12	114.895
3	13	105.88
3	14	101.015
3	15	95.3
3	16	92.124
3	17	87.071
3	18	67.161
3	19	55.829
3	20	16.715
2	1	278.676
2	2	270.159
2	3	279.71
2	4	272.591
2	5	266.701
2	6	258.457
2	7	260.062
2	8	268.448
2	9	227.359
2	10	215.866
2	11	198.514
2	12	179.856
2	13	171.234
2	14	165.944
2	15	161.638
2	16	159.788
2	17	151.862
2	18	135.376
2	19	125.595
2	20	98.863
1	1	346.731
1	2	341.995
1	3	349.773
1	4	340.789
1	5	338.01
1	6	325.182
1	7	328.339
1	8	333.462
1	9	300.839
1	10	292.52
1	11	275.064
1	12	254.504
1	13	252.279
1	14	250.211
1	15	242.438
1	16	242.713
1	17	233.577
1	18	223.335
1	19	218.322
1	20	199.88

fig = plt.figure(figsize=plt.figaspect(0.5))
ax = fig.add_subplot(1, 2, 1, projection='3d')
# note this: you can skip rows!
my_data = np.genfromtxt('data.csv', delimiter=',',skip_header=1)
X = my_data[:,0]
Y = my_data[:,1]
Z = my_data[:,2]

xi = np.linspace(X.min(),X.max(),100)
yi = np.linspace(Y.min(),Y.max(),100)
# VERY IMPORTANT, to tell matplotlib how is your data organized
zi = griddata((X, Y), Z, (xi[None,:], yi[:,None]), method='cubic')

CS = plt.contour(xi,yi,zi,15,linewidths=0.5,color='k')
ax = fig.add_subplot(1, 2, 2, projection='3d')

xig, yig = np.meshgrid(xi, yi)

surf = ax.plot_surface(xig, yig, zi,
        linewidth=0)

plt.show()