Pyspark create a summary table with calculated values - apache-spark-sql

Question

I have a data frame that looks like this:
+--------------------+---------------------+-------------+------------+-----+
|tpep_pickup_datetime|tpep_dropoff_datetime|trip_distance|total_amount|isDay|
+--------------------+---------------------+-------------+------------+-----+
| 2019-01-01 09:01:00| 2019-01-01 08:53:20| 1.5| 2.00| true|
| 2019-01-01 21:59:59| 2019-01-01 21:18:59| 2.6| 5.00|false|
| 2019-01-01 10:01:00| 2019-01-01 08:53:20| 1.5| 2.00| true|
| 2019-01-01 22:59:59| 2019-01-01 21:18:59| 2.6| 5.00|false|
+--------------------+---------------------+-------------+------------+-----+
and I want to create a summary table which calculates the trip_rate for all the night trips and all the day trips (total_amount column divided by trip_distance). So the end result should look like this:
+------------+-----------+
| day_night | trip_rate |
+------------+-----------+
|Day | 1.33 |
|Night | 1.92 |
+------------+-----------+
Here is what I'm trying to do:
df2 = spark.createDataFrame(
[
('2019-01-01 09:01:00','2019-01-01 08:53:20','1.5','2.00','true'),#day
('2019-01-01 21:59:59','2019-01-01 21:18:59','2.6','5.00','false'),#night
('2019-01-01 10:01:00','2019-01-01 08:53:20','1.5','2.00','true'),#day
('2019-01-01 22:59:59','2019-01-01 21:18:59','2.6','5.00','false'),#night
],
['tpep_pickup_datetime','tpep_dropoff_datetime','trip_distance','total_amount','day_night'] # add your columns label here
)
day_trip_rate = df2.where(df2.day_night == 'Day').withColumn("trip_rate",F.sum("total_amount")/F.sum("trip_distance"))
night_trip_rate = df2.where(df2.day_night == 'Night').withColumn("trip_rate",F.sum("total_amount")/F.sum("trip_distance"))
I don't believe I'm even approaching it the right way. And I'm getting this error:(
raise AnalysisException(s.split(': ', 1)[1], stackTrace) pyspark.sql.utils.AnalysisException: "grouping expressions sequence is empty, and 'tpep_pickup_datetime' is not an aggregate function.
Can someone help me know how to approach this to get that summary table?

Answer 1

from pyspark.sql import functions as F
from pyspark.sql.functions import *
df2.groupBy("day_night").agg(F.round(F.sum("total_amount")/F.sum("trip_distance"),2).alias('trip_rate'))\
.withColumn("day_night", F.when(col("day_night")=="true", "Day").otherwise("Night")).show()
+---------+---------+
|day_night|trip_rate|
+---------+---------+
| Day| 1.33|
| Night| 1.92|
+---------+---------+
Without rounding off:
df2.groupBy("day_night").agg(F.sum("total_amount")/F.sum("trip_distance")).alias('trip_rate')\
.withColumn("day_night", F.when(col("day_night")=="true", "Day").otherwise("Night")).show()
(You have day_night in df2 construction code, but isDay in the display table. I'm considering the field name as day_night here.)