I have created the best fit lines for the dataset using the following code:
fig, ax = plt.subplots()
for dd,KK in DATASET.groupby('Z'):
fit = polyfit(x,y,3)
fit_fn = poly1d(fit)
ax.plot(KK['x'],KK['y'],'o',KK['x'], fit_fn(KK['x']),'k',linewidth=4)
ax.set_xlabel('x')
ax.set_ylabel('y')
The graph displays the best fit line for each group of Z. I want print the equation of the best fit line on top of the line.Please suggest what can i do out here
Line of best fit refers to a line through a scatter plot of data points that best expresses the relationship between those points.
The line of best fit is described by the equation ŷ = bX + a, where b is the slope of the line and a is the intercept (i.e., the value of Y when X = 0). This calculator will determine the values of b and a for a set of data comprising two variables, and estimate the value of Y for any specified value of X.
So you need to write some function that convert a poly parameters array to a latex string, here is an example:
import pylab as pl
import numpy as np
x = np.random.randn(100)
y = 1 + 2 * x + 3 * x * x + np.random.randn(100) * 2
poly = pl.polyfit(x, y, 2)
def poly2latex(poly, variable="x", width=2):
t = ["{0:0.{width}f}"]
t.append(t[-1] + " {variable}")
t.append(t[-1] + "^{1}")
def f():
for i, v in enumerate(reversed(poly)):
idx = i if i < 2 else 2
yield t[idx].format(v, i, variable=variable, width=width)
return "${}$".format("+".join(f()))
pl.plot(x, y, "o", alpha=0.4)
x2 = np.linspace(-2, 2, 100)
y2 = np.polyval(poly, x2)
pl.plot(x2, y2, lw=2, color="r")
pl.text(x2[5], y2[5], poly2latex(poly), fontsize=16)
Here is the output:
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