I'm quite new to matplotlib and i would like to know how we can change color of points on a scatter plot based on the value in a list.
In fact, I have a 2-D array that I want to plot and a list with the same number of rows containing, for each point, the color we want to use.
#Example
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']
ax1.plot(data[:,0],data[:,1],'o',picker=True)
How to set the color parameter to fit my list of colors ?
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()
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")
You have to set argument c
of plt.scatter
with a list of desired colors:
import matplotlib.pylab as plt
import numpy as np
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']
plt.scatter(data[:,0],data[:,1],marker='o',c = colors)
plt.show()
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