nxcals.api.extraction.data.builders.DataFrame.fillna

DataFrame.fillna(value: LiteralType, subset: Optional[Union[str, Tuple[str, ...], List[str]]] = None) → DataFrame

DataFrame.fillna(value: Dict[str, LiteralType]) → DataFrame

Replace null values, alias for na.fill(). DataFrame.fillna() and DataFrameNaFunctions.fill() are aliases of each other.

New in version 1.3.1.

Parameters:

value (int, float, string, bool or dict) – Value to replace null values with. If the value is a dict, then subset is ignored and value must be a mapping from column name (string) to replacement value. The replacement value must be an int, float, boolean, or string.
subset (str, tuple or list, optional) – optional list of column names to consider. Columns specified in subset that do not have matching data type are ignored. For example, if value is a string, and subset contains a non-string column, then the non-string column is simply ignored.

Examples

>>> df4.na.fill(50).show()
+---+------+-----+
|age|height| name|
+---+------+-----+
| 10|    80|Alice|
|  5|    50|  Bob|
| 50|    50|  Tom|
| 50|    50| null|
+---+------+-----+

>>> df5.na.fill(False).show()
+----+-------+-----+
| age|   name|  spy|
+----+-------+-----+
|  10|  Alice|false|
|   5|    Bob|false|
|null|Mallory| true|
+----+-------+-----+

>>> df4.na.fill({'age': 50, 'name': 'unknown'}).show()
+---+------+-------+
|age|height|   name|
+---+------+-------+
| 10|    80|  Alice|
|  5|  null|    Bob|
| 50|  null|    Tom|
| 50|  null|unknown|
+---+------+-------+