polars.DataFrame.lazy

DataFrame.lazy() → LazyFrame

Start a lazy query from this point. This returns a LazyFrame object.

Operations on a LazyFrame are 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 [3 cols, {"a": Int64 … "c": Boolean}] at ...>