How to Add Markers to a Graph Plot in Matplotlib with Python

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 7, 11]
plt.plot(x, y, marker='o', label='Data from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 7, 11]
plt.plot(x, y, marker='s', markersize=10, markerfacecolor='red', label='Data from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y1 = [2, 3, 5, 7, 11]
y2 = [1, 4, 6, 8, 10]
plt.plot(x, y1, marker='^', label='Series 1 from how2matplotlib.com')
plt.plot(x, y2, marker='*', label='Series 2 from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 7, 11]
plt.scatter(x, y, marker='o', color='blue', label='Scatter from how2matplotlib.com')
plt.plot(x, y, marker='o', linestyle='-', color='red', label='Line from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [2, 3, 5, 7, 11]
highlight = [False, False, True, False, True]

colors = ['blue' if not h else 'red' for h in highlight]
markers = ['o' if not h else 's' for h in highlight]

for xi, yi, ci, mi in zip(x, y, colors, markers):
    plt.scatter([xi], [yi], marker=mi, color=ci)

plt.plot(x, y, label='Data from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y1 = [2, 3, 5, 7, 11]
y2 = [1, 4, 6, 8, 10]
plt.plot(x, y1, marker='o', linestyle='-', color='blue', label='Series 1 from how2matplotlib.com')
plt.plot(x, y2, marker='s', linestyle='--', color='green', label='Series 2 from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(5)
y = [2, 3, 5, 7, 11]
plt.bar(x, y, color='blue', label='Bar from how2matplotlib.com')
plt.plot(x, y, marker='d', color='red', label='Marker from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

theta = np.linspace(0, 2*np.pi, 10)
r = np.linspace(0, 10, 10)
plt.subplot(111, polar=True)
plt.plot(theta, r, marker='*', label='Polar data from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = np.random.standard_normal(100)
y = np.random.standard_normal(100)
z = np.random.standard_normal(100)
ax.scatter(x, y, z, marker='^', label='3D Scatter from how2matplotlib.com')
ax.legend()
plt.show()

import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np

fig, ax = plt.subplots()

x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(x)

line, = ax.plot(x, y, marker='o', label='Animated sine wave from how2matplotlib.com')

def update(num, x, y, line):
    line.set_data(x[:num], y[:num])
    return line,

ani = animation.FuncAnimation(fig, update, len(x), fargs=[x, y, line],
                              interval=50, blit=True)
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

data = np.random.rand(10,10)
plt.imshow(data, cmap='hot', interpolation='nearest')
plt.scatter([5], [5], color='blue', marker='o', label='Highlight from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

data = np.random.normal(0, 1, size=100)
plt.boxplot(data, notch=True, patch_artist=True)
plt.scatter([1], [np.mean(data)], color='red', marker='D', label='Mean from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt

x = np.linspace(0.1, 15, 400)
y = x ** 2
plt.semilogy(x, y, marker='o', label='Logarithmic plot from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(1, 6)
y = np.power(x, 2)  # y = x^2
yerr = np.sqrt(x)  # Error bars are the square root of x
plt.errorbar(x, y, yerr=yerr, fmt='o', marker='s', color='blue', label='Error bar plot from how2matplotlib.com')
plt.legend()
plt.show()

import matplotlib.pyplot as plt
import numpy as np

N = 5
menMeans = (20, 35, 30, 35, 27)
womenMeans = (25, 32, 34, 20, 25)
childrenMeans = (30, 32, 34, 20, 27)

ind = np.arange(N)    # the x locations for the groups
width = 0.35       # the width of the bars: can also be len(x) sequence

p1 = plt.bar(ind, menMeans, width, label='Men from how2matplotlib.com')
p2 = plt.bar(ind, womenMeans, width, bottom=menMeans, label='Women from how2matplotlib.com')
p3 = plt.bar(ind, childrenMeans, width, bottom=np.array(menMeans)+np.array(womenMeans), label='Children from how2matplotlib.com')

plt.ylabel('Scores')
plt.title('Scores by group and gender')
plt.xticks(ind, ('G1', 'G2', 'G3', 'G4', 'G5'))
plt.yticks(np.arange(0, 81, 10))
plt.legend()

plt.show()