
        
        
            
                
                
                    df = spark.createDataFrame([["Alex", 20], ["Bob", 24], ["Cathy", 22]], ["name", "age"])
df.show()
                
            
            +-----+---+
| name|age|
+-----+---+
| Alex| 20|
|  Bob| 24|
|Cathy| 22|
+-----+---+

To replace the name Alex with Doge, and others with Eric:


        
        
            
                
                
                    import pyspark.sql.functions as F
df.select(F.when(df.name == "Alex", "Doge").otherwise("Eric")).show()
                
            
            +-----------------------------------------------+
|CASE WHEN (name = Alex) THEN Doge ELSE Eric END|
+-----------------------------------------------+
|                                           Doge|
|                                           Eric|
|                                           Eric|
+-----------------------------------------------+

Note that we can replace our existing column with the new column like so:


        
        
            
                
                
                    df.name = F.when(df.name == "Alex", "Doge").otherwise("Eric")
df.show()
                
            
            +----+---+
|name|age|
+----+---+
|Doge| 25|
|Eric| 30|
|Eric| 50|
+----+---+

Published by Isshin Inada

Edited by 0 others

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Official PySpark Documentation

https://spark.apache.org/docs/latest/api/python/reference/api/pyspark.sql.Column.otherwise.html

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