TheorderBy()method in pyspark is used to order the rows of a dataframe by one or multiple columns. It has the following syntax. df.orderBy(*column_names, ascending=True) Here, The parameter*column_namesrepresents one or multiple columns by which we need to order the pyspark dataframe. The...
Group by multiple columns from pyspark.sql.functions import avg, desc df = ( auto_df.groupBy(["modelyear", "cylinders"]) .agg(avg("horsepower").alias("avg_horsepower")) .orderBy(desc("avg_horsepower")) ) # Code snippet result: +---+---+---+ |modelyear|cylinders|avg_horsepower|...
Group by multiple columns from pyspark.sql.functions import avg, desc df = ( auto_df.groupBy(["modelyear", "cylinders"]) .agg(avg("horsepower").alias("avg_horsepower")) .orderBy(desc("avg_horsepower")) ) # Code snippet result: +---+---+---+ |modelyear|cylinders|avg_horsepower|...
('person_names'))# Just take the lastest row for each combination (Window Functions)frompyspark.sqlimportWindowasWwindow=W.partitionBy("first_name","last_name").orderBy(F.desc("date"))df=df.withColumn("row_number",F.row_number().over(window))df=df.filter(F.col("row_number")==1)...