How to plot confidence interval in Python?

Question

I recently started to use Python and I can't understand how to plot a confidence interval for a given datum (or set of data). I already have a function that computes, given a set of measurements, a higher and lower bound depending on the confidence level that I pass to it, but I don't know how to use those two values to plot a confidence interval. I know that this question have been already asked here but I did not find the answers useful.

Answer 1

There are several ways to accomplish what you asking for:

Using only matplotlib

from matplotlib import pyplot as plt import numpy as np  #some example data x = np.linspace(0.1, 9.9, 20) y = 3.0 * x #some confidence interval ci = 1.96 * np.std(y)/np.sqrt(len(x))  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

Answer 2

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: