polars.LazyFrame.groupby_dynamic#
- LazyFrame.groupby_dynamic(
- index_column: IntoExpr,
- *,
- every: str | timedelta,
- period: str | timedelta | None = None,
- offset: str | timedelta | None = None,
- truncate: bool = True,
- include_boundaries: bool = False,
- closed: ClosedInterval = 'left',
- by: IntoExpr | Iterable[IntoExpr] | None = None,
- start_by: StartBy = 'window',
- check_sorted: bool = True,
Group based on a time value (or index value of type Int32, Int64).
Deprecated since version 0.19.0: This method has been renamed to
LazyFrame.group_by_dynamic()
.- Parameters:
- index_column
Column used to group based on the time window. Often of type Date/Datetime. This column must be sorted in ascending order (or, if by is specified, then it must be sorted in ascending order within each group).
In case of a dynamic group by on indices, dtype needs to be one of {Int32, Int64}. Note that Int32 gets temporarily cast to Int64, so if performance matters use an Int64 column.
- every
interval of the window
- period
length of the window, if None it is equal to ‘every’
- offset
offset of the window if None and period is None it will be equal to negative every
- truncate
truncate the time value to the window lower bound
- include_boundaries
Add the lower and upper bound of the window to the “_lower_bound” and “_upper_bound” columns. This will impact performance because it’s harder to parallelize
- closed{‘right’, ‘left’, ‘both’, ‘none’}
Define which sides of the temporal interval are closed (inclusive).
- by
Also group by this column/these columns
- start_by{‘window’, ‘datapoint’, ‘monday’, ‘tuesday’, ‘wednesday’, ‘thursday’, ‘friday’, ‘saturday’, ‘sunday’}
The strategy to determine the start of the first window by.
‘window’: Truncate the start of the window with the ‘every’ argument. Note that weekly windows start on Monday.
‘datapoint’: Start from the first encountered data point.
a day of the week (only takes effect if every contains
'w'
):‘monday’: Start the window on the Monday before the first data point.
‘tuesday’: Start the window on the Tuesday before the first data point.
…
‘sunday’: Start the window on the Sunday before the first data point.
- check_sorted
When the
by
argument is given, polars can not check sortedness by the metadata and has to do a full scan on the index column to verify data is sorted. This is expensive. If you are sure the data within the by groups is sorted, you can set this toFalse
. Doing so incorrectly will lead to incorrect output
- Returns:
- LazyGroupBy
Object you can call
.agg
on to aggregate by groups, the result of which will be sorted by index_column (but note that if by columns are passed, it will only be sorted within each by group).