Skill v1.0.0

version: "1.0.0" name: prophet description: "Meta Prophet — forecasting at scale. Additive model with yearly/weekly/daily seasonality, holiday effects, changepoints, and trend decomposition. Handles missing data and outliers automatically." tags: [prophet, forecasting, time-series, seasonality, trend, meta, zorai]

Overview

Meta Prophet forecasts time series data with additive seasonality (yearly, weekly, daily), holiday effects, changepoint detection, and trend decomposition. Handles missing data and outliers automatically. Designed for business forecasting with human-interpretable components.

Installation

uv pip install prophet

Forecast

import pandas as pd
from prophet import Prophet
import numpy as np
df = pd.DataFrame({
    "ds": pd.date_range("2023-01-01", periods=365, freq="D"),
    "y": [100 + i*0.5 + 10*(i%7==0) + np.random.normal(0, 5) for i in range(365)],
})
model = Prophet(yearly_seasonality=True, weekly_seasonality=True)
model.fit(df)
future = model.make_future_dataframe(periods=90)
forecast = model.predict(future)
model.plot(forecast)
model.plot_components(forecast)

Holidays

model = Prophet()
model.add_country_holidays("US")
model.fit(df)

References

• Prophet docs
• Prophet GitHub