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PySpark SQL Functions | lower method

Machine Learning
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PySpark
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PySpark SQL Functions
schedule Jul 1, 2022
Last updated
local_offer PySpark
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PySpark SQL Functions' lower(~) method returns a new PySpark Column with the specified column lower-cased.

Parameters

1. col | string or Column

The column to perform the lowercase 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|
+----+---+

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