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PySpark SQL Functions | upper method

schedule Aug 12, 2023
Last updated
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PySpark SQL Functions' upper(~) method returns a new PySpark Column with the specified column upper-cased.

Parameters

1. col | string or Column

The column to perform the uppercase operation on.

Return Value

A PySpark Column (pyspark.sql.column.Column).

Examples

Consider the following PySpark DataFrame:

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|
+----+---+
robocat
Published by Isshin Inada
Edited by 0 others
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