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PySpark DataFrame | transform 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 transform(~) method applies a function on the DataFrame that called this method and returns a new PySpark DataFrame.

Parameters

1. func | function

The PySpark DataFrame that called the transform(~) method.

Return Value

PySpark DataFrame.

Examples

Consider the following PySpark DataFrame:

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

Sorting the columns in ascending order by their label in PySpark DataFrame

To get a new PySpark DataFrame where the columns are sorted in ascending order:

def sort_columns(df_input):
return df_input.select(*sorted(df_input.columns))

df.transform(sort_columns).show()
+---+----+
|age|name|
+---+----+
| 25|Alex|
| 30| Bob|
+---+----+

Here, the * converts the list of column labels into positional arguments of the select(~) method.

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Published by Isshin Inada
Edited by 0 others
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