Menu
I have the following Pandas Dataframe, where column a represents a dummy variable:
What I would like to do is to give my markers a cmap='jet' color following the value of column b, except when the value in column a is equal to 1 - in this case I want it to be the color grey.
Any idea how I can do this?
755
In Matplotlib’s scatter () function, we can color the data points by a variable using “c” argument. The color argument “c” can take A scalar or sequence of n numbers to be mapped to colors using cmap and norm. A 2-D array in which the rows are RGB or RGBA.
We also add x and y-axis labels to the scatter plot made with Matplotlib. In Matplotlib’s scatter () function, we can color the data points by a variable using “c” argument. The color argument “c” can take A scalar or sequence of n numbers to be mapped to colors using cmap and norm.
Then we use the scatter () function multiple times, to create a scatter plot. We pass the color argument to the function to set the color manually. To visualize the graph, use show () method. Here we’ll learn to draw a scatter plot with a single color format. We use the parameter c to set the color of the plot and here we’ll set it to red.
Often datasets contain multiple quantitative and categorical variables and may be interested in relationship between two quantitative variables with respect to a third categorical variable. And coloring scatter plots by the group/categorical variable will greatly enhance the scatter plot.
You have to mark your values which are equal to one and plot:
import matplotlib.pyplot as plt
import numpy as np
# test data
t = np.linspace(0, 2 * np.pi, 30)
x = np.sin(t)
x[3] = 1
y = np.cos(t)
# indices for 'bad' values
indices = x == 1
# calc colors from jet cmap
cmap = plt.get_cmap('jet')
colors = cmap((y - y.min()) / y.ptp())
# normal values
plt.scatter(t[~indices], x[~indices], c = colors[~indices], cmap = cmap)
# bad values
plt.scatter(t[indices], x[indices], c = 'grey')
plt.show()
Arrays t, x, y represent pandas series.
160
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
