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python-matplotlibHow to plot bestfit curve line


In order to make curved line, we have to increase degree of our polynomial (3rd argument to polyfit()):

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, c = np.polyfit(x, y, 2)

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

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

polyfit

calculates least square polynomial fit

a * x*x + b*x + c

we plot 2-degree polynomial to get curved best fit regression line

.show()

render chart in a separate window


How to plot bestfit curve 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, c = np.polyfit(x, y, 2)

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

plt.show()