
        
        
            
                
                
                    df = spark.createDataFrame([["alex", 25], ["bOb", 30]], ["name", "age"])
df.show()
                
            
            +----+---+
|name|age|
+----+---+
|alex| 25|
| bOb| 30|
+----+---+

Uppercasing strings in PySpark DataFrame

To upper-case the strings in the name column:


        
        
            
                
                
                    import pyspark.sql.functions as F
df.select(F.upper(df.name)).show()
                
            
            +-----------+
|upper(name)|
+-----------+
|       ALEX|
|        BOB|
+-----------+

Note that passing in a column label as a string also works:


        
        
            
                
                
                    import pyspark.sql.functions as F
df.select(F.upper("name")).show()
                
            
            +-----------+
|upper(name)|
+-----------+
|       ALEX|
|        BOB|
+-----------+

Replacing column with uppercased column in PySpark

To replace the name column with the upper-cased version, use the withColumn(~) method:


        
        
            
                
                
                    import pyspark.sql.functions as F
df.withColumn("name", F.upper(df.name)).show()
                
            
            +----+---+
|name|age|
+----+---+
|ALEX| 25|
| BOB| 30|
+----+---+

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.functions.upper.html

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