Rename more than one column using withColumnRenamed

by

It is not possible to use a single withColumnRenamed call.

  • You can use DataFrame.toDF method*

    data.toDF('x3', 'x4')

    or 

    new_names = ['x3', 'x4']
data.toDF(*new_names)

  • It is also possible to rename with simple select:

    from pyspark.sql.functions import col

mapping = dict(zip(['x1', 'x2'], ['x3', 'x4']))
data.select([col(c).alias(mapping.get(c, c)) for c in data.columns])

Similarly in Scala you can:

  • Rename all columns:

    val newNames = Seq("x3", "x4")

data.toDF(newNames: _*)

  • Rename from mapping with select:

    val  mapping = Map("x1" -> "x3", "x2" -> "x4")

df.select(
  df.columns.map(c => df(c).alias(mapping.get(c).getOrElse(c))): _*
)

    or foldLeft + withColumnRenamed 

    mapping.foldLeft(data){
  case (data, (oldName, newName)) => data.withColumnRenamed(oldName, newName) 
}

* Not to be confused with RDD.toDF which is not a variadic functions, and takes column names as a list,

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