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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 + cgithub```
 `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

### 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()``````