Get first element in array Pyspark - pyspark

Question

I want to add new 2 columns value services arr first and second value
but I'm getting the error:
Field name should be String Literal, but it's 0;
production_target_datasource_df.withColumn("newcol",production_target_datasource_df["Services"].getItem(0))
+------------------+--------------------+
| cid | Services|
+------------------+--------------------+
|845124826013182686| [112931, serv1]|
|845124826013182686| [146936, serv1]|
|845124826013182686| [32718, serv2]|
|845124826013182686| [28839, serv2]|
|845124826013182686| [8710, serv2]|
|845124826013182686| [2093140, serv3]|

Answer 1

You don't have to use .getItem(0)
production_target_datasource_df["Services"][0] would be enough.
# Constructing your table:
from pyspark.sql import Row
df = sc.parallelize([Row(cid=1,Services=["2", "serv1"]),
Row(cid=1, Services=["3", "serv1"]),
Row(cid=1, Services=["4", "serv2"])]).toDF()
df.show()
+---+----------+
|cid| Services|
+---+----------+
| 1|[2, serv1]|
| 1|[3, serv1]|
| 1|[4, serv2]|
+---+----------+
# Adding the two columns:
new_df = df.withColumn("first_element", df.Services[0])
new_df = new_df.withColumn("second_element", df.Services[1])
new_df.show()
+---+----------+-------------+--------------+
|cid| Services|first_element|second_element|
+---+----------+-------------+--------------+
| 1|[2, serv1]| 2| serv1|
| 1|[3, serv1]| 3| serv1|
| 1|[4, serv2]| 4| serv2|
+---+----------+-------------+--------------+

Answer 2

As the error is saying, you need to pass a string not a 0.
Then, you wonder : what string should I pass ?
If you follow #pault advice, and printSchema, you will actually know what are the corresponding keys to your values in the list.
Here is the documentation of getItem, helping you figure this out.
Another way to know what to pass, is to simply pass any string, you could type:
production_target_datasource_df.withColumn("newcol",production_target_datasource_df["Services"].getItem('0'))
and the logs will tell you what keys were expected.
Hope this helps ;)