As convention usually the matplotlib library is imported in this way: import matplotlib.pyplot as plt plt.scatter (Xtrain, ytrain, c 'red') Share. What I see in the 3D scatter plot are only red points. You have to remove the : pyplot.scatter (Xtrain, ytrain, c 'red') ot (Xtrain, regressor.predict (Xtrain), c 'blue') PS. We will use the combination of hue and palette to color the data points in scatter plot. In this post we will see examples of making scatter plots and coloring the data points using Seaborn in Python. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped.
#Python scatter plot colors how to
for X,Y in data: scatter(X, Y, c) c: a color. The following code shows how to create a scatterplot using the variable z to color the markers based on category: import matplotlib.pyplot as plt groups df.groupby('z') for name, group in groups: plt.plot(group.x, group.y, marker'o', linestyle'', markersize12, labelname) plt.legend() You can find more Python tutorials here. How can I create a 3D plot with a color gradient for the points? See the example below, which works for a 2D scatter plot.Įdit (thanks to Chris): What I'm expecting to see from the 3D plot is a color gradient of the points ranging from red to green as in the 2D scatter plot. And coloring scatter plots by the group/categorical variable will greatly enhance the scatter plot. What's the trivial example of how to generate random colors for passing to plotting functions I'm calling scatter inside a loop and want each plot a different color.
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