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 + cimport matplotlib.pyplot as pltloads 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 |
polyfitcalculates least square polynomial fit | a*x + bwe plot 1-st degree polynomial using calculated |
.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 = np.polyfit(x, y, 1)
plt.plot(x, a*x + b)
plt.show()More of Python Matplotlib
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