pyspark.sql.functions.date_sub¶

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

Returns the date that is days days before start. If days is a negative value then these amount of days will be added to start.

New in version 1.5.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

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

Returns

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

Examples

>>> df = spark.createDataFrame([('2015-04-08', 2,)], ['dt', 'sub'])
>>> df.select(date_sub(df.dt, 1).alias('prev_date')).collect()
[Row(prev_date=datetime.date(2015, 4, 7))]
>>> df.select(date_sub(df.dt, df.sub.cast('integer')).alias('prev_date')).collect()
[Row(prev_date=datetime.date(2015, 4, 6))]
>>> df.select(date_sub('dt', -1).alias('next_date')).collect()
[Row(next_date=datetime.date(2015, 4, 9))]

pyspark.sql.functions.date_format pyspark.sql.functions.date_trunc