Using Prophet for probabilistic forecasting

In this recipe, we’ll show how to use Prophet for probabilistic forecasting.

Getting ready

Prophet is a tool developed by Facebook for forecasting time series data. It’s particularly adept at handling data with strong seasonal patterns and irregular events such as holidays. To get started with Prophet, we need to prepare our data and environment.

The process begins with loading and preprocessing the time series data so that it fits the format Prophet requires. Each time series in Prophet must have two columns – ds (the timestamp) and y (the value we wish to predict):

import pandas as pd
from prophet import Prophet
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
mvtseries = pd.read_csv(
"assets/daily_multivariate_timeseries.csv",
parse_dates=["datetime"],
)
mvtseries['ds'] = mvtseries['datetime...