I have a code that gives me a scatter plot of predicted vs actual values as a function of concentration. The data is pulled from an excel csv spreadsheet. This is the code: import matplotlib.pyplot as plt from numpy import loadtxt dataset = loadtxt("ColorPlot.csv", delimiter=',') x = dataset[:,0] y = dataset[:,1] z = dataset[:,2] scaled_z = (z - z.min()) / z.ptp() colors = plt.cm.viridis(scaled_z) sc=plt.scatter(x, y, c=colors) plt.clim(0, 100) plt.colorbar() plt.xlabel("Actual") plt.ylabel("Predicted") plt.show() And with this I get a nice graph: However if I change the color to something like colors = plt.cm.plasma(scaled_z) I get the graph below but the colorbar remains unchanged. I've tried lots of different things like cmap or edgecolors but I don't know how to change it. And I want to keep the code as simple as it currently is because I want to readily change the third variable of z based on my excel spreadsheet data. Is there also a way for the scale of the colorbar to pick up what the scale is from the excel spreadsheet without me manually specifying 0-100? Continue reading...
