Color line by third variable - Python

Question

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).

How can I do this please?

I'm not following what you mean by coloring the line by a third variable. If you have another variable, then you need another line (maybe of a different color) or a 3D plot, right? — Matt Messersmith
– Matt Messersmith, Commented Apr 8, 2016 at 17:26
Do you want the line in one color, or several? How do you choose the color? — Reblochon Masque
– Reblochon Masque, Commented Apr 8, 2016 at 17:27
I read it as "I want to express a third dimension of data / third kind of information by changing color of the segments of the line". — Jiri Tousek
– Jiri Tousek, Commented Apr 8, 2016 at 19:56

Andrew Brēza · Accepted Answer · 2024-01-05 18:13:31Z

I've written a simple function to map a given property to a color:

import matplotlib.cm as cm
import matplotlib.pyplot as plt

def plot_colourline(x,y,c):
    col = 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=col[i])
    im = ax.scatter(x, y, c=c, s=0, cmap=cm.jet)
    return im

This function normalizes the desired property and get a color from the jet colormap. The PathCollection returned by the function will also enable plotting a colorbar. 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)
im = plot_colourline(x,y,prop)
fig.colorbar(im)

screenpaver · Accepted Answer · 2016-04-08 19:12:25Z

6

You could color the data points by a third variable, if that would help:

dates = [dt.date() for dt in pd.to_datetime(df.Date)]
plt.scatter(dates, df.Price, c=df.Change, s=100, lw=0)
plt.plot(dates, df.Price)
plt.colorbar()
plt.show()

answered Apr 8, 2016 at 19:12

screenpaver

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Comments

Thomas Wagenaar · Accepted Answer · 2024-09-23 13:29:04Z

The matplotlib documentation provdes two ways coloring lines based on a third value. See multicolored lines. It for example provides the function colored_line which you can use as shown below.

# -------------- Create and show plot --------------
# Some arbitrary function that gives x, y, and color values
t = np.linspace(-7.4, -0.5, 200)
x = 0.9 * np.sin(t)
y = 0.9 * np.cos(1.6 * t)
color = np.linspace(0, 2, t.size)

# Create a figure and plot the line on it
fig1, ax1 = plt.subplots()
lines = colored_line(x, y, color, ax1, linewidth=10, cmap="plasma")
fig1.colorbar(lines)  # add a color legend

# Set the axis limits and tick positions
ax1.set_xlim(-1, 1)
ax1.set_ylim(-1, 1)
ax1.set_xticks((-1, 0, 1))
ax1.set_yticks((-1, 0, 1))
ax1.set_title("Color at each point")

plt.show()

Which results in

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