matplotlib 3d scatter from 2d numpy array vertices error
Question: I'm stumped as to why this is not working. I am pulling a bunch of floating
point data in to a numpy array from a csv file, and I just want to create a 3d
scatter plot based from 3 of the columns in the array.

    
    
    #import data from the csv file
    data = np.genfromtxt('data.csv', delimiter=',', dtype=float, skiprows=1)
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    ax.scatter(data[:,1], data[:,2], data[:,7], c='r', marker='0')
    plt.show()
    

every time i get an assertion error:

    
    
    /usr/lib/pymodules/python2.7/matplotlib/path.pyc in __init__(self, vertices, codes, _interpolation_steps, closed)
    127             codes[-1] = self.CLOSEPOLY
    128 
    --> 129         assert vertices.ndim == 2
    130         assert vertices.shape[1] == 2
    131 
    
    AssertionError:
    

I have... just figured it out, but i'll post this any way because that is the
single most useless error message i have ever encountered. the problem was
here:

    
    
    ax.scatter(data[:,1], data[:,2], data[:,7], c='r', marker='0')
    

marker='0' is invalid, i meant to hit marker='o', once fixed it works just
fine.


Answer: You can use the `scatter3D()` method of the `Axes3DSubplot` object:

    
    
    from mpl_toolkits.mplot3d import Axes3D
    
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    
    ax.scatter3D(data[:,1], data[:,2], data[:,7], c='r', marker='0')
    

