Preprocessing - Nixtla

id_time_grid(df, freq, start='per_serie', end='global', id_col='unique_id', time_col='ds')

Generate all expected combiations of ids and times. Parameters:

Name	Type	Description	Default
`df`	`pandas or polars DataFrame`	Input data	required
`freq`	`str or int`	Series’ frequency	required
`start`	`(str, int, date or datetime)`	Initial timestamp for the series. * ‘per_serie’ uses each serie’s first timestamp * ‘global’ uses the first timestamp seen in the data * Can also be a specific timestamp or integer, e.g. ‘2000-01-01’, 2000 or datetime(2000, 1, 1) Defaults to “per_serie”.	`‘per_serie’`
`end`	`(str, int, date or datetime)`	Initial timestamp for the series. * ‘per_serie’ uses each serie’s last timestamp * ‘global’ uses the last timestamp seen in the data * Can also be a specific timestamp or integer, e.g. ‘2000-01-01’, 2000 or datetime(2000, 1, 1) Defaults to “global”.	`‘global’`
`id_col`	`str`	Column that identifies each serie. Defaults to ‘unique_id’.	`‘unique_id’`
`time_col`	`str`	Column that identifies each timestamp. Defaults to ‘ds’.	`‘ds’`

Returns:

Type	Description
`DFType`	pandas or polars DataFrame: Dataframe with expected ids and times.

fill_gaps(df, freq, start='per_serie', end='global', id_col='unique_id', time_col='ds')

Enforce start and end datetimes for dataframe. Parameters:

Name	Type	Description	Default
`df`	`pandas or polars DataFrame`	Input data	required
`freq`	`str or int`	Series’ frequency	required
`start`	`(str, int, date or datetime)`	Initial timestamp for the series. * ‘per_serie’ uses each serie’s first timestamp * ‘global’ uses the first timestamp seen in the data * Can also be a specific timestamp or integer, e.g. ‘2000-01-01’, 2000 or datetime(2000, 1, 1) Defaults to “per_serie”.	`‘per_serie’`
`end`	`(str, int, date or datetime)`	Initial timestamp for the series. * ‘per_serie’ uses each serie’s last timestamp * ‘global’ uses the last timestamp seen in the data * Can also be a specific timestamp or integer, e.g. ‘2000-01-01’, 2000 or datetime(2000, 1, 1) Defaults to “global”.	`‘global’`
`id_col`	`str`	Column that identifies each serie. Defaults to ‘unique_id’.	`‘unique_id’`
`time_col`	`str`	Column that identifies each timestamp. Defaults to ‘ds’.	`‘ds’`

Returns:

Type	Description
`DFType`	pandas or polars DataFrame: Dataframe with gaps filled.