If you want to plot standard error bars, then you can use matplotlibs errorbar (see here: https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.errorbar.html)
You can also create a confidence interval as an envelope by using fill_between. There is a good example of that in the matplotlib docs:
N = 21
x = np.linspace(0, 10, 11)
y = [3.9, 4.4, 10.8, 10.3, 11.2, 13.1, 14.1, 9.9, 13.9, 15.1, 12.5]
# fit a linear curve an estimate its y-values and their error.
a, b = np.polyfit(x, y, deg=1)
y_est = a * x + b
y_err = x.std() * np.sqrt(1/len(x) +
(x - x.mean())**2 / np.sum((x - x.mean())**2))
fig, ax = plt.subplots()
ax.plot(x, y_est, '-')
ax.fill_between(x, y_est - y_err, y_est + y_err, alpha=0.2)
ax.plot(x, y, 'o', color='tab:brown')
(Taken from https://matplotlib.org/gallery/lines_bars_and_markers/fill_between_demo.html#example-confidence-bands)