**Drop**: df.na.drop() or df.na.drop(subset=['col']). **Fill**: df.na.fill(0) or fill({'col':'default'}). **Replace**: df.na.replace('old','new'). **Expression**: coalesce(col('a'), lit(0)); when(col('a').isNull(), lit(0)).otherwise(col('a')). **Aggregation**: Spark ignores NULL in sum, avg....
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