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copied!<p>I recently had the identical problem and inspiration for my solution has come from the solutions in:</p> <ol> <li><a href="https://stackoverflow.com/questions/10374930/matplotlib-annotating-a-3d-scatter-plot">Matplotlib: Annotating a 3D scatter plot</a></li> <li><a href="https://stackoverflow.com/questions/14542232/annotate-several-points-with-one-text-in-matplotlib">Annotate several points with one text in matplotlib</a></li> </ol> <p>The solution is based on creating an array of "labels", then the position of each "label" gets updated in the update_position() function.</p> <pre><code>import numpy from mpl_toolkits.mplot3d import proj3d import matplotlib.pyplot as plt import pylab def update_position(e): print "From update position" #Transform co-ordinates to get new 2D projection tX, tY, _ = proj3d.proj_transform(dataX, dataY, dataZ, ax.get_proj()) for i in range(len(dataX)): label = labels[i] label.xy = tX[i],tY[i] label.update_positions(fig.canvas.renderer) fig.canvas.draw() return #Input 3D Data data = numpy.array([[3,6,2],[4,6,2],[2,9,2],[3,6,10],[6,1,5]]) #Separate into X, Y, Z for greater clarity dataX = data[:,0] dataY = data[:,1] dataZ = data[:,2] plt.close() fig = plt.figure() ax = fig.gca(projection='3d') #3D scatter plot ax.scatter(dataX, dataY, dataZ, marker = 'o', c='b') #Transform co-ordinates to get initial 2D projection tX, tY, _ = proj3d.proj_transform(dataX, dataY, dataZ, ax.get_proj()) #Array of labels labels = [] #Loop through data points to initially annotate scatter plot #and populate labels array for i in range(len(dataX)): text='['+str(int(dataX[i]))+','+str(int(dataY[i]))+','+str(int(dataZ[i]))+']' label = ax.annotate(text, xycoords='data', xy = (tX[i], tY[i]), xytext = (-20, 20), textcoords = 'offset points', ha = 'right', va = 'top', fontsize=6, bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5), arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0')) labels.append(label) #Positions are updated when mouse button is released after rotation. fig.canvas.mpl_connect('button_release_event', update_position) fig.show() </code></pre>

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