Python Azure Databrick: 'DataFrame' object does not support item assignment

Question

I am working on Azure Databrick. I run the python script on the notebook and gets the data from the SQL. I tried to split the date time column into date and time columns. Here is the syntax of python:

    pushdown_query = "(SELECT * FROM STAGE.OutagesAndInterruptions) int_alias"
    df = spark.read.jdbc(url=jdbcUrl, table=pushdown_query, properties=connectionProperties)

    df['INTERRUPTION_DATE']=df['INTERRUPTION_TIME'].dt.date

df['INTERRUPTION_TIME'] looks like:

+-------------------+
|  INTERRUPTION_TIME|
+-------------------+
|1997-05-12 09:57:00|
|1998-03-08 13:00:00|
|1998-02-26 13:00:00|
|1998-02-26 13:00:00|
|1998-03-03 10:04:00|
|1998-05-20 09:27:00|
|1998-11-21 08:51:00|
|1998-11-27 08:44:00|
|1998-10-19 01:19:00|
|1998-10-19 01:44:00|
|2000-03-13 07:00:00|
|2000-03-19 07:30:00|
|2000-08-04 12:55:00|
|2002-09-30 18:11:00|
|2002-09-30 18:11:00|
|2002-05-06 09:22:00|
|2002-01-16 13:15:00|
|2003-01-08 15:46:00|
|2003-02-04 10:25:00|
|2003-02-04 10:25:00|
+-------------------+

When I ran the code, it throws an error message:

TypeError: 'DataFrame' object does not support item assignment
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<command-2244924718685919> in <module>
----> 1 df['INTERRUPTION_DATE']=df['INTERRUPTION_TIME'].dt.date

TypeError: 'DataFrame' object does not support item assignment

Could we create new columns in the data frame on Data frame? How can we create new columns on the data frame in Azure data bricks?

Answer 1

This should work

from pyspark.sql.types import DateType


df2 = df.withColumn('INTERRUPTION_DATE', ,df['INTERRUPTION_TIME'].cast(DateType()))

Edit After Comment:

from pyspark.sql.functions import date_format

df.select(date_format('INTERRUPTION_TIME', 'M/d/yyyy').alias('INTERRUPTION_DATE'),
          date_format('INTERRUPTION_TIME', 'h:m:s a').alias('TIME'))