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python-matplotlibHow to plot bestfit line


import matplotlib.pyplot as plt
import numpy as np

x = np.array([1, 3, 5, 7])
y = np.array([6, 6, 7, 8])
plt.plot(x, y, 'o')

a, b = np.polyfit(x, y, 1)

plt.plot(x, a*x + b)

plt.show()ctrl + c
import matplotlib.pyplot as plt

loads Matplotlib module to use plotting capabilities

[1, 3, 5, 7]

list of x coordinates of dots to plot best fit regression from

[6, 6, 7, 8]

list of y coordinates of dots to plot best fit regression from

plt.plot(x, y, 'o')

plot our dots

polyfit

calculates least square polynomial fit

a*x + b

we plot 1-st degree polynomial using calculated a and b

.show()

render chart in a separate window


How to plot bestfit line, python matplotlib

Usage example

import matplotlib.pyplot as plt
import numpy as np

x = np.array([1, 3, 5, 7])
y = np.array([6, 6, 7, 8])
plt.plot(x, y, 'o')

a, b = np.polyfit(x, y, 1)

plt.plot(x, a*x + b)

plt.show()