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PySpark Column | startswith method

schedule Aug 12, 2023
Last updated
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PySpark Column's startswith(~) method returns a column of booleans where True is given to strings that begin with the specified substring.

Parameters

1. other | string or Column

The substring or column to compare with.

Return Value

A Column object holding booleans.

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

Getting rows that start with a certain substring in PySpark DataFrame

To get rows that start with a certain substring:

from pyspark.sql import functions as F
df.filter(F.col("name").startswith("A")).show()
+----+---+
|name|age|
+----+---+
|Alex| 20|
+----+---+

Here, F.col("name").startswith("A") returns a Column object of booleans where True corresponds to values that begin with A:

df.select(F.col("name").startswith("A")).show()
+-------------------+
|startswith(name, A)|
+-------------------+
| true|
| false|
| false|
+-------------------+

We then use the PySpark DataFrame's filter(~) method to fetch rows that correspond to True.

robocat
Published by Isshin Inada
Edited by 0 others
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