skrub.Expr.skb.eval#
- Expr.skb.eval(environment=None, *, keep_subsampling=False)[source]#
Evaluate the expression.
This returns the result produced by evaluating the expression, ie running the corresponding pipeline. The result is always the output of the pipeline’s
fit_transform
– a pipeline is refitted to the provided data.If no data is provided, the values passed when creating the variables in the expression are used.
- Parameters:
- environment
dict
orNone
, optional If
None
, the initial values of the variables contained in the expression are used. If a dict, it must map the name of each variable to a corresponding value.- keep_subsampling
bool
, default=False If True, and if subsampling has been configured (see
Expr.skb.subsample()
), use a subsample of the data. By default subsampling is not applied and all the data is used.
- environment
- Returns:
- result
The result of running the computation, ie of executing the pipeline’s
fit_transform
on the provided data.
See also
Expr.skb.preview
Access the preview of the result on the variables initial values, with subsampling. Faster than
eval
but does not allow passing new data and always applies subsampling.
Examples
>>> import skrub >>> a = skrub.var('a', 10) >>> b = skrub.var('b', 5) >>> c = a + b >>> c <BinOp: add> Result: ――――――― 15 >>> c.skb.eval() 15 >>> c.skb.eval({'a': 1, 'b': 2}) 3