Technical requirements

You can download the Jupyter Notebooks and necessary datasets from this book's GitHub repository:

• Jupyter Notebook: https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-Cookbook./blob/main/code/Ch10/Chapter%2010.ipynb
• Datasets: https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-Cookbook./tree/main/datasets/Ch10

Before you start working through the recipes in this chapter, please run the following code to load the datasets and functions that will be referenced throughout:

1. Start by importing the basic libraries that will be shared across all the recipes in this chapter:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import warnings
from statsmodels.tsa.api import (kpss, adfuller,
                              seasonal_decompose, STL)
from statsmodels.tools.eval_measures import rmspe, rmse
from sklearn.metrics import mean_absolute_percentage_error as mape
from statsmodels.graphics.tsaplots import plot_acf...