polars.len#

polars.len() → Expr[source]#

Return the number of rows in the context.

This is similar to COUNT(*) in SQL.

Returns:

Expr: Expression of data type UInt32.

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [1, 2, None],
...         "b": [3, None, None],
...         "c": ["foo", "bar", "foo"],
...     }
... )
>>> df.select(pl.len())
shape: (1, 1)
┌─────┐
│ len │
│ --- │
│ u32 │
╞═════╡
│ 3   │
└─────┘

Generate an index column by using len in conjunction with int_range().

>>> df.select(
...     pl.int_range(pl.len(), dtype=pl.UInt32).alias("index"),
...     pl.all(),
... )
shape: (3, 4)
┌───────┬──────┬──────┬─────┐
│ index ┆ a    ┆ b    ┆ c   │
│ ---   ┆ ---  ┆ ---  ┆ --- │
│ u32   ┆ i64  ┆ i64  ┆ str │
╞═══════╪══════╪══════╪═════╡
│ 0     ┆ 1    ┆ 3    ┆ foo │
│ 1     ┆ 2    ┆ null ┆ bar │
│ 2     ┆ null ┆ null ┆ foo │
└───────┴──────┴──────┴─────┘