pyspark.sql.functions.dayname

pyspark.sql.functions.dayname(col)

Date and Timestamp Function: Returns the three-letter abbreviated day name from the given date.

New in version 4.0.0.

Parameters

colColumn or column name

target date/timestamp column to work on.

Returns

Column

the three-letter abbreviation of day name for date/timestamp (Mon, Tue, Wed…)

See also

pyspark.sql.functions.day()

pyspark.sql.functions.monthname()

Examples

Example 1: Extract the weekday name from a string column representing dates

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([('2015-04-08',), ('2024-10-31',)], ['dt'])
>>> df.select("*", sf.typeof('dt'), sf.dayname('dt')).show()
+----------+----------+-----------+
|        dt|typeof(dt)|dayname(dt)|
+----------+----------+-----------+
|2015-04-08|    string|        Wed|
|2024-10-31|    string|        Thu|
+----------+----------+-----------+

Example 2: Extract the weekday name from a string column representing timestamp

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([('2015-04-08 13:08:15',), ('2024-10-31 10:09:16',)], ['ts'])
>>> df.select("*", sf.typeof('ts'), sf.dayname('ts')).show()
+-------------------+----------+-----------+
|                 ts|typeof(ts)|dayname(ts)|
+-------------------+----------+-----------+
|2015-04-08 13:08:15|    string|        Wed|
|2024-10-31 10:09:16|    string|        Thu|
+-------------------+----------+-----------+

Example 3: Extract the weekday name from a date column

>>> import datetime
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([
...     (datetime.date(2015, 4, 8),),
...     (datetime.date(2024, 10, 31),)], ['dt'])
>>> df.select("*", sf.typeof('dt'), sf.dayname('dt')).show()
+----------+----------+-----------+
|        dt|typeof(dt)|dayname(dt)|
+----------+----------+-----------+
|2015-04-08|      date|        Wed|
|2024-10-31|      date|        Thu|
+----------+----------+-----------+

Example 4: Extract the weekday name from a timestamp column

>>> import datetime
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([
...     (datetime.datetime(2015, 4, 8, 13, 8, 15),),
...     (datetime.datetime(2024, 10, 31, 10, 9, 16),)], ['ts'])
>>> df.select("*", sf.typeof('ts'), sf.dayname('ts')).show()
+-------------------+----------+-----------+
|                 ts|typeof(ts)|dayname(ts)|
+-------------------+----------+-----------+
|2015-04-08 13:08:15| timestamp|        Wed|
|2024-10-31 10:09:16| timestamp|        Thu|
+-------------------+----------+-----------+