What is DS and Y in Prophet?

The input to Prophet is always a dataframe with two columns: ds and y . The ds (datestamp) column should be of a format expected by Pandas, ideally YYYY-MM-DD for a date or YYYY-MM-DD HH:MM:SS for a timestamp. The y column must be numeric, and represents the measurement we wish to forecast.

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What is seasonality Prior scale prophet?

Basically seasonality prior scale is setting the standard deviation for the normal distribution . Higher seasonality prior scale means we are setting a wider normal distribution when sampling for the 2*n terms for our fourier. At the end, the yearly components will be simply the fourier generated dot beta.

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How does Prophet forecasting work?

At its core, the Prophet procedure is an additive regression model with four main components: A piecewise linear or logistic growth curve trend. Prophet automatically detects changes in trends by selecting changepoints from the data . A yearly seasonal component modeled using Fourier series.

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Why do we use Prophet?

It is open for collaboration, and people are free to make pull requests to improve it further . One major advantage with Prophet is that it does not require much prior knowledge of forecasting time series data as it can automatically find seasonal trends with a set of data and offers easy to understand parameters.

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How good is Prophet?

It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well . Seasonal effects caused by human behavior: weekly, monthly and yearly cycles, dips and peaks on public holidays.

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