polars.Expr.fill_nan#

Expr.fill_nan( value: int | float | Expr | None, ) → Expr[source]#

Fill floating point NaN value with a fill value.

Parameters:

value: Value used to fill NaN values.

Warning

Note that floating point NaNs (Not a Number) are not missing values. To replace missing values, use fill_null().

See also

fill_null

Examples

>>> df = pl.DataFrame(
...     {
...         "a": [1.0, None, float("nan")],
...         "b": [4.0, float("nan"), 6],
...     }
... )
>>> df.with_columns(pl.col("b").fill_nan(0))
shape: (3, 2)
┌──────┬─────┐
│ a    ┆ b   │
│ ---  ┆ --- │
│ f64  ┆ f64 │
╞══════╪═════╡
│ 1.0  ┆ 4.0 │
│ null ┆ 0.0 │
│ NaN  ┆ 6.0 │
└──────┴─────┘