
        
        
            
                
                
                    df = spark.createDataFrame([("Alex", 15), ("Bob", 20), ("Cathy", 25)], ["name", "age"])
df.show()
                
            
            +-----+---+
| name|age|
+-----+---+
| Alex| 15|
|  Bob| 20|
|Cathy| 25|
+-----+---+

Getting the last value of a PySpark column

To get the last value of the name column:


        
        
            
                
                
                    df.select(F.last("name")).show()
                
            
            +----------+
|last(name)|
+----------+
|     Cathy|
+----------+

Note we can also pass a Column object instead:


        
        
            
                
                
                    import pyspark.sql.functions as F
# df.select(F.last(F.col("name"))).show()
df.select(F.last(df.name)).show()
                
            
            +----------+
|last(name)|
+----------+
|     Cathy|
+----------+

Getting the last non-null value in PySpark column

Consider the following PySpark DataFrame with null values:


        
        
            
                
                
                    df = spark.createDataFrame([("Alex", 15), ("Bob", 20), ("Cathy", None)], ["name", "age"])
df.show()
                
            
            +-----+----+
| name| age|
+-----+----+
| Alex|  15|
|  Bob|  20|
|Cathy|null|
+-----+----+

By default, ignorenulls=False, which means that the last value is returned regardless of whether it is null or not:


        
        
            
                
                
                    df.select(F.last(df.age)).show()
                
            
            +---------+
|last(age)|
+---------+
|     null|
+---------+

To return the last non-null value instead, set ignorenulls=True:


        
        
            
                
                
                    df.select(F.last(df.age, ignorenulls=True)).show()
                
            
            +---------+
|last(age)|
+---------+
|       20|
+---------+

Getting the last value of each group in PySpark

The last(~) method is also useful in aggregations. Consider the following PySpark DataFrame:


        
        
            
                
                
                    data = [("Alex", "A"), ("Alex", "B"), ("Bob", None), ("Bob", "A"), ("Cathy", "C")]
df = spark.createDataFrame(data, ["name", "class"])
df.show()
                
            
            +-----+-----+
| name|class|
+-----+-----+
| Alex|    A|
| Alex|    B|
|  Bob| null|
|  Bob|    A|
|Cathy|    C|
+-----+-----+

To get the last value of each aggregate:


        
        
            
                
                
                    df.groupby("name").agg(F.last("class")).show()
                
            
            +-----+-----------+
| name|last(class)|
+-----+-----------+
| Alex|          B|
|  Bob|          A|
|Cahty|          C|
+-----+-----------+

Here, we are grouping by name, and then for each of these group, we are obtaining the last value that occurred in the class column.

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.last.html#pyspark.sql.functions.last

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