How to left shift column value in spark sql?

I have the following table

Team	Team_Category	Score1	Score2	Score3	Score4	Score5	Score6	Score7	Score8
A41	Bikes	40			91			51
A57	Bicycles					60			47

I want to left shift the values if a previous score is NULL or ""
The required output is:

Team	Team_Category	Score1	Score2	Score3	Score4	Score5	Score6	Score7	Score8
A41	Bikes	40	91	51
A57	Bicycles	60	47

I tried using coalesce like

spark.sql("""SELECT Team, Team_Category, COALESCE(NULLIF(Score1,""),NULLIF(Score2,""),...NULLIF(Score8,"")) AS Score1, COALESCE(NULLIF(Score2,""),NULLIF(Score3,"")...NULLIF(Score8,"")) AS Score2,...""")

but this would only solve half the problem. Even though the values will now be moved to the left, the values on the right will still be there.

How can this be done using spark sql?

Note: A team can have multiple rows, but they are independent from each other.

Solution

Create an array from the Score columns then use array_compact to remove nulls finally based on the new position of each element in the array reassign the scores columns back to the dataframe

cols = [c for c in df.columns if c.startswith('Score')]

arr = F.array_compact(F.array(*cols))
df1 = df.select('Team', 'Team_Category', *[arr[i].alias(c) for i, c in enumerate(cols)])

+----+-------------+------+------+------+------+------+------+------+------+
|Team|Team_Category|Score1|Score2|Score3|Score4|Score5|Score6|Score7|Score8|
+----+-------------+------+------+------+------+------+------+------+------+
| A41|        Bikes|    40|    91|    51|  null|  null|  null|  null|  null|
| A57|     Bicycles|    60|    47|  null|  null|  null|  null|  null|  null|
+----+-------------+------+------+------+------+------+------+------+------+

Note: array_compact is only available starting from spark 3.4.0 if you are using an old version then we can use filter insstead: arr = F.filter(F.array(*cols), lambda x: x.isNotNull())