Assign a color gradient to markers in matplotlib based on data

Question

I'm plotting some scatter plots with matplotlib and need to have the marker colors change based on another series of data that I'm not plotting. So it will be a normal XY plot, but the marker colors change based on an unplotted z-axis, essentially. Anyone know how to do this?

Edit: here's the code I'm using

import matplotlib.pyplot as plt
import pandas as pd

fig = plt.figure(figsize=(7, 7), dpi=150)
ax = plt.subplot()

csv = pd.read_csv('FvmTest.csv', index_col='Id')  
data = csv[['CO2max', 'd13c']] 

bdata = data.loc['b'] 

bx = bdata['CO2max']                               
by = bdata['d13c'] 

plt.plot(bx, by, 'b.', label='bdata')  

plt.suptitle('CO2max vs d13c', fontsize=16)
plt.xlabel('CO2max', fontsize=14)
plt.ylabel('d13c', fontsize=14)

plt.show()

Can you post your code you wrote so far please ? – samubreizhizel Nov 13 '17 at 18:55 — samubreizhizel, Nov 13 '17 at 18:55

score -1 · Answer 1 · answered Nov 13 '17 at 18:58

You're going to want to set c = z and z is whatever you're basing the color on

ax.scatter(x, y, c = z, s = 200, cmap='rainbow')

s is the size of the points, you're going to want to choose a size that is large enough that you can see the colors, and you need to select a colormap.

Assign a color gradient to markers in matplotlib based on data

1 Answers1