Prophet - Time Series Forecasting Library

What is Prophet?

Prophet is an open-source time series forecasting library developed by Facebook. It is designed to handle a wide range of time series data, including daily, weekly, and monthly data, and works well with missing data and outliers. Prophet is particularly suited for business time series data, such as sales, revenue, and user growth.

How does Prophet work?

Prophet uses a decomposable time series model, which consists of three main components: trend, seasonality, and holidays. The trend component captures the overall direction of the time series data, while the seasonality component models periodic fluctuations in the data. The holiday component accounts for any irregularities or special events that may affect the time series.

Prophet is implemented in both Python and R, and its API is designed to be intuitive and easy to use, making it accessible to users without extensive time series forecasting experience.

Example of using Prophet in Python:

To use Prophet, you first need to install the package:

$ pip install fbprophet

Here’s a simple example of using Prophet to forecast time series data:

import pandas as pd
from fbprophet import Prophet

# Load the example data
df = pd.read_csv('example_data.csv')

# Initialize a Prophet model
model = Prophet()

# Fit the model to the data

# Make future predictions
future = model.make_future_dataframe(periods=365)
forecast = model.predict(future)

# Plot the forecast
fig = model.plot(forecast)

Additional resources on Prophet: