Prophet Forecasting Tutorial

This tutorial will guide you through the process of time series forecasting using the Prophet library. Prophet is a forecasting tool developed by Facebook for analyzing time series data and making predictions.

Overview

Prophet is particularly suited for data with daily observations that have strong seasonal effects and several holidays. It is also known for its ease of use and its ability to handle missing data and outliers.

Key Features

Seasonality:自动检测和调整季节性。
Holidays:支持添加节假日影响。
Missing Values:可以处理数据中的缺失值。
Outliers:能够识别和调整异常值。

Getting Started

Before you begin, make sure you have Python installed on your system. You can install Prophet using pip:

pip install fbprophet

Installation

If you haven't installed Prophet yet, you can do so by running the following command:

pip install fbprophet

Quick Start

Here's a simple example to get you started:

from fbprophet import Prophet

# Create a Prophet object
m = Prophet()

# Fit the model
m.fit(df)

# Make a future dataframe
future = m.make_future_dataframe(periods=365)

# Predict future values
forecast = m.predict(future)

# Plot the forecast
m.plot(forecast)

Advanced Topics

Custom Seasonality: Learn how to customize the seasonality of your model.
Categorical Variables: Incorporate categorical variables for additional context.
Cross-validation: Understand how to perform cross-validation for better model performance.