Dropping Nulls:
We can remove rows containing null values using the drop method. For example:
df.dropna()
Filling Nulls:
We can replace null values with a specified constant or a calculated value using the fillna method:
df.fillna(value)
Handling Null in Sql Queries:
When working with Spark SQL, we can use the COALESCE or IFNULL functions to handle nulls in SQL queries.
Handling null values depends on the specific use case and the nature of the data.
It’s essential to carefully choose a strategy that aligns with the goals of analysis or processing.