pyspark.sql.functions.to_date#

pyspark.sql.functions.to_date(col, format=None)[source]#

Converts a Column into pyspark.sql.types.DateType using the optionally specified format. Specify formats according to datetime pattern. By default, it follows casting rules to pyspark.sql.types.DateType if the format is omitted. Equivalent to col.cast("date").

New in version 2.2.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colColumn or column name: input column of values to convert.
format: literal string, optional: format to use to convert date values.

Returns

Column: date value as pyspark.sql.types.DateType type.

See also

pyspark.sql.functions.to_timestamp()
pyspark.sql.functions.to_timestamp_ltz()
pyspark.sql.functions.to_timestamp_ntz()
pyspark.sql.functions.to_utc_timestamp()
pyspark.sql.functions.try_to_timestamp()
pyspark.sql.functions.date_format()

Examples

>>> import pyspark.sql.functions as sf
>>> df = spark.createDataFrame([('1997-02-28 10:30:00',)], ['ts'])
>>> df.select('*', sf.to_date(df.ts)).show()
+-------------------+-----------+
|                 ts|to_date(ts)|
+-------------------+-----------+
|1997-02-28 10:30:00| 1997-02-28|
+-------------------+-----------+

>>> df.select('*', sf.to_date('ts', 'yyyy-MM-dd HH:mm:ss')).show()
+-------------------+--------------------------------+
|                 ts|to_date(ts, yyyy-MM-dd HH:mm:ss)|
+-------------------+--------------------------------+
|1997-02-28 10:30:00|                      1997-02-28|
+-------------------+--------------------------------+