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 1

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')