Preparing a multivariate time series for supervised learning

The first recipe of this chapter addresses the problem of preparing a multivariate time series for supervised learning. We’ll show how the sliding window method we used in the previous chapter can be extended to solve this task. Then, we’ll demonstrate how to prepare a time series using TimeSeriesDataSet, a PyTorch Forecasting class that handles the preprocessing steps of time series.

Getting ready

We’ll use the same time series we analyzed in Chapter 1. We’ll need to load the dataset with pandas using the following code:

import pandas as pd
data = pd.read_csv('assets/daily_multivariate_timeseries.csv',
                   parse_dates=['Datetime'],
                   index_col=&apos...