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PySpark SQL Functions
Method arrayMethod colMethod collect_listMethod collect_setMethod concatMethod concat_wsMethod countMethod count_distinctMethod countDistinctMethod date_formatMethod dayofmonthMethod dayofweekMethod dayofyearMethod element_atMethod explodeMethod exprMethod firstMethod greatestMethod instrMethod lastMethod leastMethod lengthMethod litMethod lowerMethod maxMethod meanMethod minMethod monthMethod regexp_extractMethod regexp_replaceMethod repeatMethod roundMethod splitMethod to_dateMethod translateMethod trimMethod upperMethod whenMethod year
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PySpark SQL Functions | trim method
Machine Learning
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schedule Jul 1, 2022
Last updated local_offer PySpark
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expand_more PySpark SQL Functions' trim(~)
method returns a new PySpark column with the string values trimmed, that is, with the leading and trailing spaces removed.
Parameters
1. col
| string
The column of type string
to trim.
Return Value
A new PySpark Column.
Examples
Consider the following PySpark DataFrame:
+---------+---+| name|age|+---------+---+| Alex | 20|| Bob| 30||Cathy | 40|+---------+---+
Here, the values in the name
column have leading and trailing spaces.
Trimming columns in PySpark
To trim the name
column, that is, to remove the leading and trailing spaces:
Here, the alias(~)
method is used to assign a label to the Column
returned by trim(~)
.
To get the original PySpark DataFrame but with the name
column updated with the trimmed version, use the withColumn(~)
method:
+-----+---+| name|age|+-----+---+| Alex| 20|| Bob| 30||Cathy| 40|+-----+---+
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Published by Isshin Inada
Edited by 0 others
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Official PySpark Documentation
https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.sql.functions.trim.html
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