Hands-On Exploratory Data Analysis with Python

Fundamentals of TSA

In order to understand the time series dataset, let's randomly generate a normalized dataset:

1. We can generate the dataset using the numpy library:

import osimport numpy as np%matplotlib inlinefrom matplotlib import pyplot as pltimport seaborn as snszero_mean_series = np.random.normal(loc=0.0, scale=1., size=50)zero_mean_series

We have used the NumPy library to generate random datasets. So, the output given here will be different for you. The output of the preceding code is given here:

array([-0.73140395, -2.4944216 , -1.44929237, -0.40077112, 0.23713083, 0.89632516, -0.90228469, -0.96464949, 1.48135275, 0.64530002, -1.70897785, 0.54863901, -1.14941457, -1.49177657, -2.04298133, 1.40936481, 0.65621356, -0.37571958, -0.04877503, ...