Using a line plot plt.plot()
plt.plot()
does only allow for a single color. So you may simply loop over the data and colors and plot each point individually.
import numpy as np
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
data = np.array([[4.29488806,-5.34487081],
[3.63116248,-2.48616998],
[-0.56023222,-5.89586997],
[-0.51538502,-2.62569576],
[-4.08561754,-4.2870525 ],
[-0.80869722,10.12529582]])
colors = ['red','red','red','blue','red','blue']
for xy, color in zip(data, colors):
ax.plot(xy[0],xy[1],'o',color=color, picker=True)
plt.show()
Using scatter plot plt.scatter()
In order to produce a scatter plot, use scatter
. This has an argument c
, which allows numerous ways of setting the colors of the scatter points.
(a) One easy way is to supply a list of colors.
colors = ['red','red','red','blue','red','blue']
ax.scatter(data[:,0],data[:,1],c=colors,marker="o", picker=True)
(b) Another option is to supply a list of data and map the data to color using a colormap
colors = [0,0,0,1,0,1] #red is 0, blue is 1
ax.scatter(data[:,0],data[:,1],c=colors,marker="o", cmap="bwr_r")