[python] Matplotlib scatterplot; colour as a function of a third variable

I want to make a scatterplot (using matplotlib) where the points are shaded according to a third variable. I've got very close with this:

plt.scatter(w, M, c=p, marker='s')

where w and M are the datapoints and p is the variable I want to shade with respect to.
However I want to do it in greyscale rather than colour. Can anyone help?

Sometimes you may need to plot color precisely based on the x-value case. For example, you may have a dataframe with 3 types of variables and some data points. And you want to do following,

• Plot points corresponding to Physical variable 'A' in RED.
• Plot points corresponding to Physical variable 'B' in BLUE.
• Plot points corresponding to Physical variable 'C' in GREEN.

In this case, you may have to write to short function to map the x-values to corresponding color names as a list and then pass on that list to the plt.scatter command.

x=['A','B','B','C','A','B']
y=[15,30,25,18,22,13]

# Function to map the colors as a list from the input list of x variables
def pltcolor(lst):
    cols=[]
    for l in lst:
        if l=='A':
            cols.append('red')
        elif l=='B':
            cols.append('blue')
        else:
            cols.append('green')
    return cols
# Create the colors list using the function above
cols=pltcolor(x)

plt.scatter(x=x,y=y,s=500,c=cols) #Pass on the list created by the function here
plt.grid(True)
plt.show()

In matplotlib grey colors can be given as a string of a numerical value between 0-1.
For example c = '0.1'

Then you can convert your third variable in a value inside this range and to use it to color your points.
In the following example I used the y position of the point as the value that determines the color:

from matplotlib import pyplot as plt

x = [1, 2, 3, 4, 5, 6, 7, 8, 9]
y = [125, 32, 54, 253, 67, 87, 233, 56, 67]

color = [str(item/255.) for item in y]

plt.scatter(x, y, s=500, c=color)

plt.show()

There's no need to manually set the colors. Instead, specify a grayscale colormap...

import numpy as np
import matplotlib.pyplot as plt

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

# Plot...
plt.scatter(x, y, c=y, s=500)
plt.gray()

plt.show()

Or, if you'd prefer a wider range of colormaps, you can also specify the cmap kwarg to scatter. To use the reversed version of any of these, just specify the "_r" version of any of them. E.g. gray_r instead of gray. There are several different grayscale colormaps pre-made (e.g. gray, gist_yarg, binary, etc).

import matplotlib.pyplot as plt
import numpy as np

# Generate data...
x = np.random.random(10)
y = np.random.random(10)

plt.scatter(x, y, c=y, s=500, cmap='gray')
plt.show()