# FORECAST

The `FORECAST`

commands lets you forecast a time series, given a time and a column to predict.
The command will append many columns to the output - the most important is `forecast`

,
which is the column we are predicting on.

The underlying model to our forecasting uses Prophet, created by Facebook.

# Syntax

`FORECAST(<column_name>, [, time=<time_column>, horizon=<horizon>])`

`column_name`

the input column name to forecast on. This must be a numerical input.`time`

is the column name of the time column. This column must have the format YYYY-MM-DD HH:MM:SS or YYYY-MM-DD.- The default is
`ds`

. Replace this if your time column is another time.

- The default is

# Returns

The command will append many column to the output, described below:

`forecast`

is the median forecasted value.`forecast_upper`

is the 90th quantile forecast value.`forecast_lower`

is the 10th quantile forecast value.`trend`

is the median trend of the forecast.`trend_upper`

is the 90th quantile trend of the forecast.`trend_lower`

is the 10th quantile trend of the forecast.`weekly`

is the median weekly trend of the forecast.`weekly_upper`

is the 90th quantile weekly trend of the forecast.`weekly_lower`

is the 10th quantile weekly trend of the forecast.`yearly`

is the median yearly trend of the forecast.`yearly_upper`

is the 90th quantile yearly trend of the forecast.`yearly_lower`

is the 10th quantile yearly trend of the forecast.

# Examples

Forecast the number of bookings in the next year.

`SELECT * FROM airbnb FORECAST(total_bookings, time=date, horizon=365)`