Using a column value as a parameter to a spark DataFrame function

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One option is to use pyspark.sql.functions.expr, which allows you to use columns values as inputs to spark-sql functions.

Based on @user8371915’s comment I have found that the following works:

from pyspark.sql.functions import expr

df.select(
    '*',
    expr('posexplode(split(repeat(",", rpt), ","))').alias("index", "col")
).where('index > 0').drop("col").sort('letter', 'index').show()
#+------+---+-----+
#|letter|rpt|index|
#+------+---+-----+
#|     X|  3|    1|
#|     X|  3|    2|
#|     X|  3|    3|
#|     Y|  1|    1|
#|     Z|  2|    1|
#|     Z|  2|    2|
#+------+---+-----+

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