If I have a scatter plot like this MWE:
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(5)
fig = plt.figure()
ax = fig.add_subplot(111)
xlist = []
ylist = []
for i in range(500):
x = np.random.normal(100)
xlist.append(x)
y = np.random.normal(5)
ylist.append(y)
x_ave = np.average(x)
y_ave = np.average(y)
plt.scatter(xlist, ylist)
plt.scatter(x_ave, y_ave, c = 'red', marker = '*', s = 50)
what's the easiest way to plot the 'average point' (is there a proper word for that?) on the plot? All of the tutorials and examples I've found show how to plot the line of best fit, but I just want the single point.
Plotting (x_ave, y_ave)
works, but is there a better way, especially since I'd eventually want to show the standard deviations with error bars too?