I've got a lot of points to plot and am noticing that plotting them individually in matplotlib takes much longer (more than 100 times longer, according to cProfile) than plotting them all at once.

However, I need to color code the points (based on data associated with each one) and can't figure out how to plot more than one color for a given call to Axes.plot(). For example, I can get a result similar to the one I want with something like

fig, ax = matplotlib.pyplot.subplots()
rands = numpy.random.random_sample((10000,))
for x in range(10000):ax.plot(x, rands[x], 'o', color=str(rands[x]))
matplotlib.pyplot.show()

but would rather do something much faster like

fig, ax = matplotlib.pyplot.subplots()
rands = numpy.random.random_sample((10000,))
# List of colors doesn't work
ax.plot(range(10000), rands, 'o', color=[str(y) for y in rands])
matplotlib.pyplot.show()

but providing a list as the value for color doesn't work in this way.

Is there a way to provide a list of colors (and for that matter, edge colors, face colors , shapes, z-order, etc.) to Axes.plot() so that each point can potentially be customized, but all points can be plotted at once?

Using Axes.scatter() seems to get part way there, since it allows for individual setting of point color; but color is as far as that seems to go. (Axes.scatter() also lays out the figure completely differently.)

It is about 5 times faster for me to create the objects (patches) directly. To illustrate the example, I have changed the limits (which have to be set manually with this method). The circle themselves are draw with matplotlib.path.Path.circle. Minimal working example:

import numpy as np
import pylab as plt
from matplotlib.patches import Circle
from matplotlib.collections import PatchCollectionfig, ax = plt.subplots(figsize=(10,10))
rands = np.random.random_sample((N,))patches = []
colors  = []for x in range(N):C = Circle((x/float(N), rands[x]), .01)colors.append([rands[x],rands[x],rands[x]])patches.append(C)plt.axis('equal')
ax.set_xlim(0,1)
ax.set_ylim(0,1)collection = PatchCollection(patches)
collection.set_facecolor(colors)
ax.add_collection(collection)
plt.show()