patito.DataFrame.fill_null

DataFrame.fill_null(value=None, strategy=None, limit=None, matches_supertype=True)

Fill null values using a filling strategy, literal, or Expr.

If "default" is provided as the strategy, the model fields with default values are used to fill missing values.

Parameters:

  • value (Optional[Any]) – Value used to fill null values.

  • strategy (Optional[Literal['forward', 'backward', 'min', 'max', 'mean', 'zero', 'one', 'defaults']]) – Accepts the same arguments as polars.DataFrame.fill_null in addition to "defaults" which will use the field’s default value if provided.

  • limit (Optional[int]) – The number of consecutive null values to forward/backward fill. Only valid if strategy is "forward" or "backward".

  • matches_supertype (bool) – Fill all matching supertype of the fill value.

Returns:

A new dataframe with nulls filled in according to the provided strategy parameter.

Return type:

DataFrame[Model]

Example

>>> import patito as pt
>>> class Product(pt.Model):
...     name: str
...     price: int = 19
...
>>> df = Product.DataFrame(
...     {"name": ["apple", "banana"], "price": [10, None]}
... )
>>> df.fill_null(strategy="defaults")
shape: (2, 2)
┌────────┬───────┐
│ name   ┆ price │
│ ---    ┆ ---   │
│ str    ┆ i64   │
╞════════╪═══════╡
│ apple  ┆ 10    │
│ banana ┆ 19    │
└────────┴───────┘