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PySpark DataFrame | take method

Machine Learning
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PySpark
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PySpark DataFrame
schedule Jul 1, 2022
Last updated
local_offer PySpark
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PySpark DataFrame's take(~) method returns the first num number of rows as a list of Row objects.

Parameters

1. num | integer

The number of rows to return.

Return Value

A list of Row objects.

Examples

Consider the following PySpark DataFrame:

df = spark.createDataFrame([["Alex", 25], ["Bob", 30], ["Cathy", 40]], ["name", "age"])
df.show()
+-----+---+
| name|age|
+-----+---+
| Alex| 25|
| Bob| 30|
|Cathy| 40|
+-----+---+

Getting the first n number of rows of PySpark DataFrame as list of Row objects

To get the first n number of rows as list of Row objects:

df.take(2)
[Row(name='Alex', age=25), Row(name='Bob', age=30)]

Difference between methods take(~) and head(~)

The difference between methods takes(~) and head(~) is takes always return a list of Row objects, whereas head(~) will return just a Row object in the case when we set head(n=1).

For instance, consider the following PySpark DataFrame:

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

Invoking take(1) yields:

df.take(1)
[Row(name='Alex', age=20)]

Invoking head(1) yields:

df.head(1)
[Row(name='Alex', age=20)]

For all other values of n, the methods take(~) and head(~) yield the same output.

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Published by Isshin Inada
Edited by 0 others
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