Setting ticks on matplotlib 3-D plots - python-3.x

Question

I'm doing some cluster analysis and want to use matplotlib to visualise the results. For the most part, this is working out OK. However, I'm struggling with controlling tick placement on the axes. That is, the ticks on the y axis are overcrowded and I'd like to thin them out. I've tried supplying a range for the ticks using the numpy arrange function, but this isn't working.
I don't know if this is because I'm not familiar enough with matplotlib, or if it's an issue with 3-D plotting. In any event, I've tried all the solutions I can find on Stack and nothing seems to be working.
My code:
import matplotlib.pyplot as plt
import matplotlib.cm as cm
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(data['col_1'], data['col_2'], data['col_3'], c = data.index, cmap = cm.winter, s=60)
ax.view_init(15, 240)
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis')
ax.set_zlabel('Z- Axis')
plt.title('Sample Plot')
plt.show()
My solution to this is to supply the ticks as follows:
ticks = np.arange(0.3, 0.7, 0.02)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(data['col_1'], data['col_2'], data['col_3'], c = data.index, cmap = cm.winter, s=60)
ax.view_init(15, 240)
ax.set_xticks(ticks)
ax.set_yticks(ticks)
ax.set_zticks(ticks)
ax.set_xlabel('X Axis')
ax.set_ylabel('Y Axis')
ax.set_zlabel('Z- Axis')
plt.title('Sample Bad Plot')
plt.show()
However, this only produces the hot mess below. Any help to be had?

Answer 1

The problem is that your x-values lie approximately within the range 0.54-0.68, your y-values lie within the range 0.34-0.42 and your z-values lie within the range0.55-0.63. Now in your second code, you define ticks = np.arange(0.3, 0.7, 0.02) which creates ticks from 0.3 to 0.68 and then you assign these values to be displayed on x, y, z axis using ax.set_xticks(ticks) and so on. You get this mess because your supplied ticks values are outside the range of actual x, y, z data points. Since you are only interested in refining the y axis ticks, you can just do
ticks = np.arange(0.34, 0.44, 0.02)
and then just set the ticks for the y axis as
ax.set_yticks(ticks).
If you don't want to specify the numbers 0.34 and 0.44 manually, you can find the maximum and minimum y value and use something like ticks = np.arange(min_value, max_value, 0.02).
Since I do not have access to your original data data['col_1'] and so on, I can't play with your code but the above tips will surely help.