pyspark.sql.functions.try_to_date#

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

This is a special version of try_to_date that performs the same operation, but returns a NULL value instead of raising an error if date cannot be created.

New in version 4.0.0.

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',)], ['ts'])
>>> df.select('*', sf.try_to_date(df.ts)).show()
+----------+---------------+
|        ts|try_to_date(ts)|
+----------+---------------+
|1997-02-28|     1997-02-28|
+----------+---------------+

>>> df.select('*', sf.try_to_date('ts', 'yyyy-MM-dd')).show()
+----------+---------------------------+
|        ts|try_to_date(ts, yyyy-MM-dd)|
+----------+---------------------------+
|1997-02-28|                 1997-02-28|
+----------+---------------------------+

>>> df = spark.createDataFrame([('foo',)], ['ts'])
>>> df.select(sf.try_to_date(df.ts)).show()
+---------------+
|try_to_date(ts)|
+---------------+
|           NULL|
+---------------+