pyflink.dataframe.dataframe.DataFrame.fill_nan

DataFrame.fill_nan(value: Any, subset: List[str] | None = None) → DataFrame

Replace NaN values with a given value in float columns.

Does NOT replace null — use fill_null() for that. Non-float columns in subset are silently ignored since NaN only applies to float/double types.

Parameters:

• value – The value to replace NaN with.

• subset – Column names to fill. If None, fills all float columns.

Returns:

A new DataFrame with NaN values replaced.

Example::

>>> df.fill_nan(0.0)                 # fill all float columns
>>> df.fill_nan(0.0, subset=["a"])   # fill only float column "a"