Time shift of a datetime column Pyspark

I have an issue with this code, the printed event_start_at and event_end_at change when passed in events_as_df pyspark dataframe. Does someone know what is happening here ?

import datetime
from pyspark.sql import types as T

start_date = '2019-10-01T00:00:00Z'
stop_date = '2019-10-30T00:00:00Z'

event_start_at = datetime.datetime.strptime(start_date, '%Y-%m-%dT%H:%M:%SZ')
event_end_at = datetime.datetime.strptime(stop_date, '%Y-%m-%dT%H:%M:%SZ')

print(event_start_at)
print(event_end_at)

schema = T.StructType([T.StructField('event_start_at', T.TimestampType(), True),
                       T.StructField('event_end_at', T.TimestampType(), True)])


events_as_df = spark.createDataFrame([(event_start_at, event_end_at)], schema)
events_as_df.show()

Output :

2019-10-01 00:00:00
2019-10-30 00:00:00

+-------------------+-------------------+
|     event_start_at|       event_end_at|
+-------------------+-------------------+
|2019-10-01 02:00:00|2019-10-30 01:00:00|
+-------------------+-------------------+

Thank you