pyflink.dataframe.DataFrame.drop_null

DataFrame.drop_null(subset: Optional[List[str]] = None) → pyflink.dataframe.dataframe.DataFrame

Drop rows containing null values.

Does NOT drop rows with NaN — use drop_nan() for that.

Parameters

subset – Column names to check. If None, checks all columns.

Returns

A new DataFrame with rows containing nulls removed.

Example::

>>> df.drop_null()               # drop if any column is null
>>> df.drop_null(subset=["a"])    # drop if column "a" is null