pyspark.sql.functions.dateadd¶

pyspark.sql.functions.dateadd(start: ColumnOrName, days: Union[ColumnOrName, int]) → pyspark.sql.column.Column[source]¶

Returns the date that is days days after start. If days is a negative value then these amount of days will be deducted from start.

New in version 3.5.0.

Parameters

startColumn or str: date column to work on.
daysColumn or str or int: how many days after the given date to calculate. Accepts negative value as well to calculate backwards in time.

Returns

Column: a date after/before given number of days.

Examples

>>> import pyspark.sql.functions as sf
>>> spark.createDataFrame(
...     [('2015-04-08', 2,)], ['dt', 'add']
... ).select(sf.dateadd("dt", 1)).show()
+---------------+
|date_add(dt, 1)|
+---------------+
|     2015-04-09|
+---------------+

>>> import pyspark.sql.functions as sf
>>> spark.createDataFrame(
...     [('2015-04-08', 2,)], ['dt', 'add']
... ).select(sf.dateadd("dt", sf.lit(2))).show()
+---------------+
|date_add(dt, 2)|
+---------------+
|     2015-04-10|
+---------------+

>>> import pyspark.sql.functions as sf
>>> spark.createDataFrame(
...     [('2015-04-08', 2,)], ['dt', 'add']
... ).select(sf.dateadd("dt", -1)).show()
+----------------+
|date_add(dt, -1)|
+----------------+
|      2015-04-07|
+----------------+

pyspark.sql.functions.date_trunc

pyspark.sql.functions.datediff