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PySpark SQL Functions | length 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' length(~) method returns a new PySpark Column holding the lengths of string values in the specified column.

Parameters

1. col | string or Column

The column whose string values' length will be computed.

Return Value

A new PySpark Column.

Examples

Consider the following PySpark DataFrame:

df = spark.createDataFrame([["Alex", 20], ["Bob", 30], ["Cathy", 40]], ["name", "age"])
df.show()
+-----+---+
| name|age|
+-----+---+
| Alex| 20|
| Bob| 30|
|Cathy| 40|
+-----+---+

Computing the length of column strings in PySpark

To compute the length of each value of the name column, use the length(~) method:

import pyspark.sql.functions as F
df.select(F.length("name")).show()
+------------+
|length(name)|
+------------+
| 4|
| 3|
| 5|
+------------+

We could also pass in a Column object instead of a column label like so:

# df.select(F.length(df.name)).show()
df.select(F.length(F.col("name"))).show()
+------------+
|length(name)|
+------------+
| 4|
| 3|
| 5|
+------------+

Note that we can append a new column containing the length of the strings using withColumn(~):

df_new = df.withColumn("name_length", F.length("name"))
df_new.show()
+-----+---+-----------+
| name|age|name_length|
+-----+---+-----------+
| Alex| 20| 4|
| Bob| 30| 3|
|Cathy| 40| 5|
+-----+---+-----------+
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Published by Isshin Inada
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