[Python] Spark DataFrame TimestampType - how to get Year, Month, Day values from field?

I have Spark DataFrame with take(5) top rows as follows:

import datetime

[Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=1, value=638.55),
Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=2, value=638.55),
Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=3, value=638.55),
Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=4, value=638.55),
Row(date=datetime.datetime(1984, 1, 1, 0, 0), hour=5, value=638.55)]


It's schema is defined as:

elevDF.printSchema()

root
|-- date: timestamp (nullable = true)
|-- hour: long (nullable = true)
|-- value: double (nullable = true)


How do I get the Year, Month, Day values from the 'date' field?

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