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Extract the year of a given date/timestamp as integer.
For the corresponding Databricks SQL function, see year function.
Syntax
from pyspark.databricks.sql import functions as dbf
dbf.year(col=<col>)
Parameters
| Parameter | Type | Description |
|---|---|---|
col |
pyspark.sql.Column or str |
target date/timestamp column to work on. |
Returns
pyspark.sql.Column: year part of the date/timestamp as integer.
Examples
from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([('2015-04-08',), ('2024-10-31',)], ['dt'])
df.select("*", dbf.typeof('dt'), dbf.year('dt')).show()
df = spark.createDataFrame([('2015-04-08 13:08:15',), ('2024-10-31 10:09:16',)], ['ts'])
df.select("*", dbf.typeof('ts'), dbf.year('ts')).show()
import datetime
df = spark.createDataFrame([
(datetime.date(2015, 4, 8),),
(datetime.date(2024, 10, 31),)], ['dt'])
df.select("*", dbf.typeof('dt'), dbf.year('dt')).show()
import datetime
df = spark.createDataFrame([
(datetime.datetime(2015, 4, 8, 13, 8, 15),),
(datetime.datetime(2024, 10, 31, 10, 9, 16),)], ['ts'])
df.select("*", dbf.typeof('ts'), dbf.year('ts')).show()