Q:

How can I connect points on a 3D scatter plot?

So currently, I have all these coordinates and so it's quite easy to create a 3D scatter plot of all the combination of coordinates.
fig = plt.figure(figsize=(20,10))
ax = plt.axes(projection='3d')

z = numpy.transpose(z_coords_row)[0:100]
x = numpy.transpose(x_coords_row)[0:100]
y = numpy.transpose(y_coords_row)[0:100]

plt.xticks(numpy.arange(-1.5, 1.5, .25))
plt.yticks(numpy.arange(-1.5, 1.5, .5))

ax.scatter(x, y, z,s=1)
ax.view_init(elev=10., azim=45)

This code gives me a result as so: http://i.stack.imgur.com/KKw1D.png
I've run into lots of problems trying to connect each point with a line to the next point in sequence. How do I go about connecting each point with the next in the array so that it's a smooth line graph?

A:

If you have enough points using only your coordinates I think what you are looking for is plot3D. If you need it more smooth line it might be worth looking into scipy.interpolate.RegularGridInterpolator which would help generate more points, which you could then insert into plot3D.
Example of usage of plot3D:
import numpy
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure(figsize=(20,10))
ax = plt.axes(projection='3d')

z_coords_row = numpy.sin(numpy.linspace(0,2*numpy.pi,100))+5
x_coords_row = numpy.sin(numpy.linspace(0,2*numpy.pi,100))
y_coords_row = numpy.cos(numpy.linspace(0,2*numpy.pi,100))

z = numpy.transpose(z_coords_row)[0:100]
x = numpy.transpose(x_coords_row)[0:100]
y = numpy.transpose(y_coords_row)[0:100]

plt.xticks(numpy.arange(-1.5, 1.5, .25))
plt.yticks(numpy.arange(-1.5, 1.5, .5))

ax.scatter(x, y, z,s=5)
ax.plot3D(x,y,z)
ax.view_init(elev=10., azim=45)

