polars.DataFrame.lazy#
- DataFrame.lazy() LazyFrame[source]#
Start a lazy query from this point. This returns a
LazyFrameobject.Operations on a
LazyFrameare not executed until this is requested by either calling:.fetch()(run on a small number of rows)
.collect()(run on all data)
.describe_plan()(print unoptimized query plan)
.describe_optimized_plan()(print optimized query plan)
.show_graph()(show (un)optimized query plan as graphviz graph)
Lazy operations are advised because they allow for query optimization and more parallelization.
- Returns:
- LazyFrame
Examples
>>> df = pl.DataFrame( ... { ... "a": [None, 2, 3, 4], ... "b": [0.5, None, 2.5, 13], ... "c": [True, True, False, None], ... } ... ) >>> df.lazy() <LazyFrame at ...>