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In this short how-to article, we will learn how to group DataFrame rows into a list in Pandas and PySpark. Groups will be based on the distinct values in a column. The values will be taken from another column and combined into a list.
The rows are grouped using the groupby function and then we will apply the list constructor to the column that contains the values. We can perform this task as follows:
Members = df.groupby("Team", as_index=False).agg( Members = ("Member", list) )
To do this operation in PySpark, we can use the collect_list function along with the groupby.
from pyspark.sql import functions as F Members = df.groupby("Team").agg(F.collect_list("Member"))
How to Get a List of DataFrame Column Names?
How to Select Rows From a DataFrame Based on a List of Values?
