pyspark.sql.functions.month

pyspark.sql.functions.month(col)

Extract the month of a given date/timestamp as integer.

New in version 1.5.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colColumn or column name

target date/timestamp column to work on.

Returns

Column

month part of the date/timestamp as integer.

See also

pyspark.sql.functions.year()

pyspark.sql.functions.quarter()

pyspark.sql.functions.day()

pyspark.sql.functions.hour()

pyspark.sql.functions.minute()

pyspark.sql.functions.second()

pyspark.sql.functions.monthname()

pyspark.sql.functions.extract()

pyspark.sql.functions.datepart()

pyspark.sql.functions.date_part()

Examples

Example 1: Extract the month 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.month('dt')).show()
+----------+----------+---------+
|        dt|typeof(dt)|month(dt)|
+----------+----------+---------+
|2015-04-08|    string|        4|
|2024-10-31|    string|       10|
+----------+----------+---------+

Example 2: Extract the month 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.month('ts')).show()
+-------------------+----------+---------+
|                 ts|typeof(ts)|month(ts)|
+-------------------+----------+---------+
|2015-04-08 13:08:15|    string|        4|
|2024-10-31 10:09:16|    string|       10|
+-------------------+----------+---------+

Example 3: Extract the month 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.month('dt')).show()
+----------+----------+---------+
|        dt|typeof(dt)|month(dt)|
+----------+----------+---------+
|2015-04-08|      date|        4|
|2024-10-31|      date|       10|
+----------+----------+---------+

Example 3: Extract the month 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.month('ts')).show()
+-------------------+----------+---------+
|                 ts|typeof(ts)|month(ts)|
+-------------------+----------+---------+
|2015-04-08 13:08:15| timestamp|        4|
|2024-10-31 10:09:16| timestamp|       10|
+-------------------+----------+---------+