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").

Added 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. A column that evaluates to a string, date, or timestamp.
format: literal string, optional: format to use to convert date values. A column that evaluates to a string.

Returns:

Column: date value as pyspark.sql.types.DateType type. Returns a column that evaluates to a date.

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()
pyspark.sql.functions.try_to_date()

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|
+-------------------+--------------------------------+