withColumnRenamed

Returns a new DataFrame by renaming an existing column. This is a no-op if the schema doesn't contain the given column name.

Syntax

withColumnRenamed(existing: str, new: str)

Parameters

Parameter	Type	Description
existing	str	The name of the existing column to be renamed.
new	str	The new name to be assigned to the column.

Returns

DataFrame: A new DataFrame with renamed column.

Examples

Python

df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"])

df.withColumnRenamed("age", "age2").show()
# +----+-----+
# |age2| name|
# +----+-----+
# |   2|Alice|
# |   5|  Bob|
# +----+-----+

df.withColumnRenamed("non_existing", "new_name").show()
# +---+-----+
# |age| name|
# +---+-----+
# |  2|Alice|
# |  5|  Bob|
# +---+-----+

df.withColumnRenamed("age", "age2").withColumnRenamed("name", "name2").show()
# +----+-----+
# |age2|name2|
# +----+-----+
# |   2|Alice|
# |   5|  Bob|
# +----+-----+