title: Python joining adjacent points with line in 3D scatter plot
body: <p>I have got two sets of (x,y.z) coordinates which I plotted in a 3D scatter plot with Matplotlib. Now, I would like to connect each resulting quadrilateral with a plane surface.
  I've seen how to draw a 2D polygon in a 3D space from <a href="https://stackoverflow.com/questions/4622057/plotting-3d-polygons-in-python-matplotlib">Plotting 3D Polygons in python-matplotlib</a>.</p>
  
  <p>What I don't know how to do is to group the points of my set into 4 points groups in order to draw polygons. I would be happy even if I managed to connect each point with its neighbours with a straight line.</p>
  
  <p>My set of points lies very close to a planar distribution; but it is just a set of coordinates, there is no constraint underneath it.<a href="https://i.stack.imgur.com/xs8mf.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/xs8mf.png" alt="enter image description here"></a></p>
  
  <p>My code:</p>
  
  <pre><code>import numpy as np
  from mpl_toolkits.mplot3d import Axes3D
  import matplotlib.pyplot as plt
  
  def plot_figure(data):
      fig = plt.figure()
      ax = fig.gca(projection='3d')
  
      ax.scatter(data[:, 0], data[:, 1], data[:, 2],
             c='r', s=20, linewidths=None)
  
      ax.axis('equal')
      ax.axis('tight')
  
      plt.show()
  
  
  data = [[ 1900., 800., 442.82], [ 1900., 900., 463.04], [ 1900.,1000., 
  473.06], [ 1900.,1100., 485.07], 
  [ 1900.,1200., 498.63], [ 1900.,1300., 513.83], [ 1900.,1400., 536.1 ], [ 
  1900.,1500., 551.29],
  [ 1900.,1600., 566.5 ], [ 1900.,1700., 581.65], [ 1900.,1800., 603.91], [ 
  2000., 800., 453.5 ], 
  [ 2000., 900., 473.75], [ 2000.,1000., 487.14], [ 2000.,1100., 499.48], [ 
  2000.,1200., 513.39],
  [ 2000.,1300., 528.92], [ 2000.,1400., 551.85], [ 2000.,1500., 567.35], [ 
  2000.,1600., 582.9 ], 
  [ 2000.,1700., 598.4 ], [ 2000.,1800., 621.32], [ 2100., 800., 464.23], [ 
  2100., 900., 485.34],
  [ 2100.,1000., 502.87], [ 2100.,1100., 515.71], [ 2100.,1200., 530.13], [ 
  2100.,1300., 546.14], 
  [ 2100.,1400., 570.05], [ 2100.,1500., 586.1 ], [ 2100.,1600., 602.15], [ 
  2100.,1700., 618.15], 
  [ 2100.,1800., 642.09], [ 2200., 800., 474.94], [ 2200., 900., 498.72], [ 
  2200.,1000., 516.91], 
  [ 2200.,1100., 530.09], [ 2200.,1200., 544.83], [ 2200.,1300., 561.2 ], [ 
  2200.,1400., 585.8 ], 
  [ 2200.,1500., 602.17], [ 2200.,1600., 618.55], [ 2200.,1700., 634.89], [ 
  2200.,1800., 659.46], 
  [ 2300., 800., 487.69], [ 2300., 900., 513.43], [ 2300.,1000., 532.64], [ 
  2300.,1100., 546.32], 
  [ 2300.,1200., 561.57], [ 2300.,1300., 578.43], [ 2300.,1400., 604.03], [ 
  2300.,1500., 620.89], 
  [ 2300.,1600., 637.76], [ 2300.,1700., 654.62], [ 2300.,1800., 680.23], [ 
  2400., 800., 500.75], 
  [ 2400., 900., 526.83], [ 2400.,1000., 546.69], [ 2400.,1100., 560.71], [ 
  2400.,1200., 576.3 ], 
  [ 2400.,1300., 593.52], [ 2400.,1400., 619.78], [ 2400.,1500., 636.98], [ 
  2400.,1600., 654.2 ], 
  [ 2400.,1700., 671.38], [ 2400.,1800., 697.66], [ 2500., 800., 516.1 ], [ 
  2500., 900., 542.71], 
  [ 2500.,1000., 563.6 ], [ 2500.,1100., 578.12], [ 2500.,1200., 594.18], [ 
  2500.,1300., 611.89],
  [ 2500.,1400., 639.17], [ 2500.,1500., 656.87], [ 2500.,1600., 674.58], [ 
  2500.,1700., 692.26],
  [ 2500.,1800., 719.53], [ 2600., 800., 530.05], [ 2600., 900., 556.98], [ 
  2600.,1000., 578.51],
  [ 2600.,1100., 593.37], [ 2600.,1200., 609.77], [ 2600.,1300., 627.81], [ 
  2600.,1400., 655.76],
  [ 2600.,1500., 673.82], [ 2600.,1600., 691.86], [ 2600.,1700., 709.87], [ 
  2600.,1800., 737.83]]
  data = np.asarray(data)
  
  plot_figure (data)
  </code></pre>