PySpark - get row number for each row in a group

Question

Using pyspark, I\'d like to be able to group a spark dataframe, sort the group, and then provide a row number. So

Group    Date
  A      2000
  A      2002
          


        

Answer 1

Use window function:

from pyspark.sql.window import *
from pyspark.sql.functions import row_number

df.withColumn("row_num", row_number().over(Window.partitionBy("Group").orderBy("Date")))

Answer 2

The accepted solution almost has it right. Here is the solution based on the output requested in the question:

df = spark.createDataFrame([("A", 2000), ("A", 2002), ("A", 2007), ("B", 1999), ("B", 2015)], ["Group", "Date"])

+-----+----+
|Group|Date|
+-----+----+
|    A|2000|
|    A|2002|
|    A|2007|
|    B|1999|
|    B|2015|
+-----+----+

# accepted solution above


from pyspark.sql.window import *
from pyspark.sql.functions import row_number

df.withColumn("row_num", row_number().over(Window.partitionBy("Group").orderBy("Date")))


# accepted solution above output


+-----+----+-------+
|Group|Date|row_num|
+-----+----+-------+
|    B|1999|      1|
|    B|2015|      2|
|    A|2000|      1|
|    A|2002|      2|
|    A|2007|      3|
+-----+----+-------+

As you can see, the function row_number starts from 1 and not 0 and the requested question wanted to have the row_num starting from 0. Simple change like I have made below:

df.withColumn("row_num", row_number().over(Window.partitionBy("Group").orderBy("Date"))-1).show()

Output :

+-----+----+-------+
|Group|Date|row_num|
+-----+----+-------+
|    B|1999|      0|
|    B|2015|      1|
|    A|2000|      0|
|    A|2002|      1|
|    A|2007|      2|
+-----+----+-------+

Then you can sort the "Group" column in whatever order you want. The above solution almost has it but it is important to remember that row_number begins with 1 and not 0.