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PySpark DataFrame
Method aliasMethod coalesceMethod collectMethod colRegexMethod corrMethod countMethod covMethod describeMethod distinctMethod dropMethod dropDuplicatesMethod dropnaMethod exceptAllMethod fillnaMethod filterMethod foreachMethod groupByMethod headMethod intersectMethod intersectAllMethod joinMethod limitMethod orderByMethod printSchemaMethod randomSplitMethod repartitionMethod replaceMethod sampleMethod sampleByMethod selectMethod selectExprMethod showMethod sortMethod summaryMethod tailMethod takeMethod toDFMethod toJSONMethod toPandasMethod transformMethod unionMethod unionByNameMethod whereMethod withColumnMethod withColumnRenamedProperty columnsProperty dtypesProperty rdd
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PySpark DataFrame | take method
Machine Learning
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schedule Jul 1, 2022
Last updated local_offer PySpark
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expand_more 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:
+-----+---+| 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:
[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:
+----+---+|name|age|+----+---+|Alex| 20|| Bob| 30|+----+---+
Invoking take(1)
yields:
df.take(1)
[Row(name='Alex', age=20)]
Invoking head(1)
yields:
[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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Official PySpark Documentation
https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.sql.DataFrame.take.html
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