Reset a pandas DataFrame index
An exploration of the benefits of switching from the popular Python library Pandas to the newer Polars for data manipulation tasks, highlighting improvements in performance, concurrency, and ease of use.
3.1 Getting all map Keys from DataFrame MapType column
df.withColumn("rank", rank().over(Window.partitionBy("Dept_id").orderBy($"salary".desc)))
.filter($"rank" <= 3)
.drop("rank")
.filter($"rank" <= 3)
.drop("rank")
mport org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.functions.{rank, desc}
val n: Int = ???
// Window definition
val w = Window.partitionBy($"user").orderBy(desc("rating"))
// Filter
df.withColumn("rank", rank.over(w)).where($"rank" <= n)
import org.apache.spark.sql.functions.{rank, desc}
val n: Int = ???
// Window definition
val w = Window.partitionBy($"user").orderBy(desc("rating"))
// Filter
df.withColumn("rank", rank.over(w)).where($"rank" <= n)
