ray.data.Dataset.max
ray.data.Dataset.max#
- Dataset.max(on: Optional[Union[str, List[str]]] = None, ignore_nulls: bool = True) Union[Any, Dict[str, Any]] [source]#
Return the maximum of one or more columns.
Note
This operation will trigger execution of the lazy transformations performed on this dataset.
Examples
>>> import ray >>> ray.data.range(100).max("id") 99 >>> ray.data.from_items([ ... {"A": i, "B": i**2} ... for i in range(100) ... ]).max(["A", "B"]) {'max(A)': 99, 'max(B)': 9801}
- Parameters
on – a column name or a list of column names to aggregate.
ignore_nulls – Whether to ignore null values. If
True
, null values are ignored when computing the max; ifFalse
, when a null value is encountered, the output isNone
. This method considersnp.nan
,None
, andpd.NaT
to be null values. Default isTrue
.
- Returns
The max result.
For different values of
on
, the return varies:on=None
: an dict containing the column-wise max of all columns,on="col"
: a scalar representing the max of all items in column"col"
,on=["col_1", ..., "col_n"]
: an n-column dict containing the column-wise max of the provided columns.
If the dataset is empty, all values are null. If
ignore_nulls
isFalse
and any value is null, then the output isNone
.