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PySpark Column | substr method

Machine Learning
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PySpark
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PySpark Column
schedule Jul 1, 2022
Last updated
local_offer PySpark
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PySpark Column's substr(~) method returns a Column of substrings extracted from string column values.

Parameters

1. startPos | int or Column

The starting position. This position is inclusive and non-index, meaning the first character is in position 1. Negative position is allowed here as well - please consult the example below for clarification.

2. length | int or Column

The length of the substring to extract.

Return Value

A Column object.

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|
+-----+---+

Extracting substrings from column values in PySpark DataFrame

To extract substrings from column values:

from pyspark.sql import functions as F
df.select(F.col("name").substr(2,3).alias("short_name")).show()
+----------+
|short_name|
+----------+
| lex|
| ob|
| ath|
+----------+

Note the following:

  • the F.col("name").substr(2,3) means that we are extracting a substring starting from the 2nd character and up to a length of 3.

  • even if the string is too short (e.g. "Bob"), no error will be thrown.

  • alias(~) method is used to assign a label to our column.

Note that you could also specify a negative starting position like so:

df.select(F.col("name").substr(-3,2).alias("short_name")).show()
+----------+
|short_name|
+----------+
| le|
| Bo|
| th|
+----------+

Here, we are starting from the third character from the end (inclusive).

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Published by Isshin Inada
Edited by 0 others
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