I have the following data set:
In[55]: usdbrl
Out[56]:
Date Price Open High Low Change STD
0 2016-03-18 3.6128 3.6241 3.6731 3.6051 -0.31 0.069592
1 2016-03-17 3.6241 3.7410 3.7449 3.6020 -3.16 0.069041
2 2016-03-16 3.7422 3.7643 3.8533 3.7302 -0.62 0.068772
3 2016-03-15 3.7656 3.6610 3.7814 3.6528 2.83 0.071474
4 2016-03-14 3.6618 3.5813 3.6631 3.5755 2.23 0.070348
5 2016-03-11 3.5820 3.6204 3.6692 3.5716 -1.09 0.076458
6 2016-03-10 3.6215 3.6835 3.7102 3.6071 -1.72 0.062977
7 2016-03-09 3.6849 3.7543 3.7572 3.6790 -1.88 0.041329
8 2016-03-08 3.7556 3.7826 3.8037 3.7315 -0.72 0.013700
9 2016-03-07 3.7830 3.7573 3.7981 3.7338 0.63 0.000000
I want to plot Price against Date:
But I would like to color the line by a third variable (in my case Date or Change).
Could anybody help with this please?
Thanks.
I've wrote a simple function to map a given property into a color:
import matplotlib.cm as cm
import matplotlib.pyplot as plt
def plot_colourline(x,y,c):
c = cm.jet((c-np.min(c))/(np.max(c)-np.min(c)))
ax = plt.gca()
for i in np.arange(len(x)-1):
ax.plot([x[i],x[i+1]], [y[i],y[i+1]], c=c[i])
return
This function normalizes the desired property and get a color from the jet colormap. You may want to use a different one. Then, get the current axis and plot different segments of your data with a different colour. Because I am doing a for loop, you should avoid using it for a very large data set, however, for normal purposes it is useful.
Consider the following example as a test:
import numpy as np
import matplotlib.pyplot as plt
n = 100
x = 1.*np.arange(n)
y = np.random.rand(n)
prop = x**2
fig = plt.figure(1, figsize=(5,5))
ax = fig.add_subplot(111)
plot_colourline(x,y,prop)
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