After applying pivot you need to perform an aggregate, in this case the aggregate is first as the count metric has already been computed.

from pyspark.sql import functions as F

df = spark.createDataFrame([(123, 1, 1, ), 
                            (245, 1, 3), 
                            (123, 2, 5),], 
                           ("hashtag_id", "user_id", "count", ))

df.groupBy("user_id")\
  .pivot("hashtag_id")\
  .agg(F.first("count"))\
  .show()

Output

+-------+---+----+
|user_id|123| 245|
+-------+---+----+
|      1|  1|   3|
|      2|  5|null|
+-------+---+----+