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

Lowercasing strings in PySpark DataFrame

To lower-case the strings in the name column:


        
        
            
                
                
                    import pyspark.sql.functions as F
df.select(F.lower(df.name)).show()
                
            
            +-----------+
|lower(name)|
+-----------+
|       alex|
|        bob|
+-----------+

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


        
        
            
                
                
                    import pyspark.sql.functions as F
df.select(F.lower("name")).show()
                
            
            +-----------+
|lower(name)|
+-----------+
|       alex|
|        bob|
+-----------+

Replacing column with lowercased column in PySpark

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


        
        
            
                
                
                    import pyspark.sql.functions as F
df.withColumn("name", F.lower(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.lower.html

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