How to plot confidence interval in Python?

There are several ways to accomplish what you asking for:

Using only matplotlib

from matplotlib import pyplot as pltimport numpy as np#some example datax= np.linspace(0.1, 9.9, 20)y = 3.0 * x#some confidence intervalci = 1.96 * np.std(y)/np.mean(y)fig, ax = plt.subplots()ax.plot(x,y)ax.fill_between(x, (y-ci), (y+ci), color='b', alpha=.1)

fill_between does what you are looking for. For more information on how to use this function, see: https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.fill_between.html

Output

Alternatively, go for seaborn, which supports this using lineplot or regplot,see: https://seaborn.pydata.org/generated/seaborn.lineplot.html

Let's assume that we have three categories and lower and upper bounds of confidence intervals of a certain estimator across these three categories:

data_dict = {}data_dict['category'] = ['category 1','category 2','category 3']data_dict['lower'] = [0.1,0.2,0.15]data_dict['upper'] = [0.22,0.3,0.21]dataset = pd.DataFrame(data_dict)

You can plot the confidence interval for each of these categories using the following code:

for lower,upper,y in zip(dataset['lower'],dataset['upper'],range(len(dataset))):    plt.plot((lower,upper),(y,y),'ro-',color='orange')plt.yticks(range(len(dataset)),list(dataset['category']))

Resulting with the following graph: