Update values of an array in Pyspark Dataframe

user_15173778 0
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I want to check if last two values of the array in PySpark Dataframe is [1, 0] and update it to [1, 1]

Input Dataframe

Column1    Array_column
abc        [0,1,1,0]
def        [1,1,0,0]
adf        [0,0,1,0]

Output Dataframe

Column1    Array_column
abc        [0,1,1,1]
def        [1,1,0,0]
adf        [0,0,1,1]
pyspark apache-spark-sql apache-spark
3 Answers
 >>> def udf1(i):
      if (i[2]==1) & (i[3]==0):
       i[3]=1
      else:
        i[3]=i[3]
      return i

>>> udf2=udf(udf1)
df1.withColumn("Array_Column",udf2(col("Array_Column"))).show()



+-------+------------+
|Column1|Array_Column|
+-------+------------+
|    abc|[0, 1, 1, 1]|
|    def|[1, 1, 0, 0]|
|    adf|[0, 0, 1, 1]|
+-------+------------+
user_104767650

You can slice the array, do a case when for the last two elements, and combine the two slices using concat.

import pyspark.sql.functions as F

df2 = df.withColumn(
    'Array_column',
    F.expr("""
        concat(
            slice(Array_column, 1, size(Array_column) - 2),
            case when slice(Array_column, size(Array_column) - 1, 2) = array(1,0) 
                 then array(1,1)
                 else slice(Array_column, size(Array_column) - 1, 2)
            end
         )
    """)
)

df2.show()
+-------+------------+
|Column1|Array_column|
+-------+------------+
|    abc|[0, 1, 1, 1]|
|    def|[1, 1, 0, 0]|
|    adf|[0, 0, 1, 1]|
+-------+------------+
user_141657300

You can combine array functions with when expression :

from pyspark.sql import functions as F

df1 = df.withColumn(
    "Array_column",
    F.when(
        F.slice("Array_column", -2, 2) == F.array(F.lit(1), F.lit(0)),
        F.flatten(F.array(F.expr("slice(Array_column, 1, size(Array_column) - 2)"), F.array(F.lit(1), F.lit(1))))
    ).otherwise(F.col("Array_column"))
)

df1.show()

#+-------+------------+
#|Column1|Array_column|
#+-------+------------+
#|    abc|[0, 1, 1, 1]|
#|    def|[1, 1, 0, 0]|
#|    adf|[0, 0, 1, 1]|
#+-------+------------+
user_13865510
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