## prophet.prophet()


Fit Prophet model and generate forecast.


Usage

``` python
prophet.prophet(
    train,
    params,
    test=None,
    horizon=None,
    seed=None,
)
```


## Parameters


`train: pd.DataFrame`  
Historic training data.

`params: ProphetParams`  
Parameters controlling the model.

`test: pd.DataFrame | None = None`  
Data containing the dates to forecast in a `ds` column. Typically a held-out test set or cross-validation fold.

`horizon: int | None = None`  
Number of days to forecast, after the final date in `train`. To be used if there is no test set (e.g., if actually predicting into future with no data to compare against).

`seed: int | None = None`  
Random seed (as randomness is used by prophet when estimating the prediction intervals, so a seed is needed to make them reproducible).


## Returns


`forecast: pd.DataFrame`  
Forecast dataframe.